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Joe Rogan Experience #2521 - Aravind Srinivas

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Joe Rogan Experience #2521 - Aravind Srinivas

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4386 segments

0:01

Joe Rogan podcast. Check it out.

0:03

>> The Joe Rogan Experience.

0:06

>> TRAIN BY DAY. JOE ROGAN PODCAST BY

0:08

NIGHT. All day.

0:14

>> Good to see you.

0:14

>> You too. Thanks for having me.

0:16

>> My pleasure.

0:17

>> Yeah.

0:17

>> How many podcasts have you done?

0:19

>> I don't know. I don't know the count,

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but maybe tens.

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>> Well, when we were talking, we were

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talking in the lobby. I was like this

0:26

good dude would be a good guess because

0:27

we were talking about ancient Hindu

0:29

scriptures where you were talking to me

0:31

about something that sounds like a

0:32

nuclear bomb.

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>> Yeah.

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>> And I was like oh

0:34

>> the brahmastra

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>> I need to know more about this.

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>> Yeah. So um the brahmastra is part of

0:40

the mahabarat.

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>> I mean you've talked about Mahabharat in

0:44

a bunch and

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>> Yeah. Yeah. So the mahabharat is one of

0:48

the two Hindu epics. The other one is

0:51

Ramayan. But Mahabarat's more

0:53

interesting. It's more complicated. It's

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like a lot of different stories interled

0:57

together. And um the brahmastra is the

1:00

equivalent of the hydrogen bomb.

1:03

>> And how is it described?

1:05

>> It's described as a weapon of like mass

1:07

destruction going to inhalate like human

1:10

population. Should not be used at any

1:13

cost. There's like a moral contract.

1:15

Like you you clearly have to be like,

1:17

you know, violating so many things at at

1:20

a deeply moral level to even like wield

1:23

it.

1:24

And um it's not actually it's not

1:27

actually accessible to most warriors.

1:29

There's probably like two warriors in

1:31

the world in in in in that era who were

1:34

allowed to use it. And um and it and it

1:38

has to be passed through special access

1:39

like a teacher has to like pass it on to

1:41

you the secret to use it almost like a

1:44

new think of it as like the equivalent

1:45

of a nuclear code, right? And um Arjuna

1:49

had it uh this this this uh particular

1:51

character in Mahabharat called Arjuna.

1:53

Um he was allowed to use it. Um and then

1:56

this other person was this basically

1:59

Arjuna had a teacher named Dona and um

2:02

Dona had a son named Ashwatama

2:05

and um Ashwatama was always jealous of

2:08

Arjuna. Arjuna was not Drona's son but

2:11

he was his model disciple and so Drona

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passed on the secret of the brahmastra

2:15

to him and um um

2:19

Drona's son also wanted it but because

2:22

it was his son he also passed on the

2:24

secret to his son even though the son

2:25

wasn't as good as Arjuna and at there

2:27

was the during the war Arjuna and fought

2:30

on the opposite sides it it's it's just

2:33

you know circumstances and uh and and

2:37

and his and his dad died Asham was that

2:39

the teacher died in the war and so the

2:42

son got mad and like unleashed the

2:44

brahmastra and uh Lord Krishna had to

2:47

come and save save the planet to not not

2:50

get that destruction force.

2:52

>> How old is the Mahabraata?

2:55

>> Um again it's there's a lot of different

2:58

opinions on this so I don't actually

3:00

know for sure. My understanding is is at

3:02

least 1,500 to 2,500 years old. Like

3:06

like,500 years ago is the minimum. 2,500

3:10

years ago is the maximum. So it happened

3:12

in some period in in that thousand-y

3:14

year time frame between that. And um

3:17

there's still like it's it's still

3:19

unclear if like a lot of it is just like

3:21

you know been mythologized. Um and what

3:25

actually happened was just a war between

3:28

kins. Uh there were two groups of

3:30

people. the Panda and the Kawas and um

3:34

you know each side thought they were

3:35

fighting for their own rights and

3:38

justice but um at the end of the day you

3:40

can crudely understand it as like

3:43

essentially fight for the kingdom. Um,

3:46

basically there were like there there

3:48

was a previous generation and two

3:50

brothers and they and both the brothers

3:52

had a bunch of kids and those kids were

3:54

waring to get the next in line and um

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that ended up being like a massive war

4:01

and a bunch of other allies fought on

4:02

each sides and um um so many amazing

4:06

weapons were used as part of the war and

4:08

a lot of these weapons are like

4:11

extremely like like described an extreme

4:13

level of detail that is pretty in

4:15

incredible like the there's a lot of

4:17

detail around like targeted weapons so

4:20

you could precisely identify a target

4:22

and just shoot at that. Um and then uh

4:25

>> does it explain like what the weapon is?

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>> Yeah. So there's one weapon called the

4:29

Dastra where you can just specifically

4:32

target any any particular person or

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group and it would just automatically

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direct itself and do it almost like a

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semi-autonomous

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weapon. And then Lord Krishna had this

4:43

um weapon called the sudan chakra. It's

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basically a discus and then you can just

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release it and it'll go and specifically

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identify somebody and chop up their head

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and come back to your you right. It it

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self-directs itself. So my what I was

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amazed by is how um interesting it is in

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terms of

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um all the autonomy in the weapons semi-

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autonomy or autonomy where the weapons

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could just be directed at people or like

5:12

directed at you know a group of soldiers

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and it would just go and do its job and

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come back to the wielder and um um there

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were so many different astras wunastra

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nagastra remastra is obviously the

5:23

ultimate the the hydrogen bomb

5:25

equivalent and all of these are

5:27

described in a lot of detail and like

5:29

who has access to it and of course it's

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it's mythologized. So it's described as

5:33

this like these arrows in your like back

5:36

of your uh shoulders, but you could you

5:38

could understand it as like you know

5:40

somebody having just access to a lot of

5:42

weapons and then um whoever was powerful

5:44

would go capture and colonize and like

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gain power and um essentially a a fight

5:51

between a group of cousins. That that

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that that's the bottom line of that

5:55

story. Now, if we think of history as

5:57

this linear progression from caveman to

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us, Yeah. and we hear about autonomous

6:01

weapons that were written in the

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Mahabraata somewhere around 2,000 plus

6:05

years ago, we go, well, a mythology.

6:07

>> Yeah.

6:08

>> But if not, if there's been some sort of

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rise and fall of civilization, if there

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has been catastrophic,

6:15

>> whatever it is, asteroid impacts,

6:18

shifting of the poles, whatever it is,

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>> it's caused great disasters. You can

6:23

imagine that these people are

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remembering a time where there was some

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sort of very advanced civilization. And

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this is what they're describing. Like if

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you knew for a fact that there had been

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a great advanced technologically

6:37

advanced civilization when we have

6:39

>> evidence that they had some technology

6:41

like the pyramids of Giza and stuff like

6:43

how did you do that? I don't how there's

6:44

some technology involved, right?

6:46

>> Yeah.

6:46

>> But we don't have evidence of the

6:48

technology. But if we did, if we knew,

6:50

you would look at the Mahabat and go,

6:52

"Oh, this is history." They're just

6:54

explaining it in a kind of crude

6:57

contemporary way for the time. Arrows

7:00

instead of, you know, semi-autonomous

7:02

drones with exploding heads on them.

7:05

>> Yeah.

7:05

>> I mean, that's what we have now. All

7:07

those things that they're describing,

7:10

hydrogen bomb, semi-autonomous and

7:12

autonomous drones. I mean, they have

7:15

they have autonomous fighter jets now.

7:17

like they don't need people anymore.

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Like this we're we're in that area right

7:21

now. So when you read about something

7:23

like that from the Mahabarata, you go

7:24

like okay what what was really going on?

7:27

>> Exactly. Yeah. I mean that that's always

7:29

been my fascination with with with those

7:31

epics and uh the level of detail with

7:34

which they described all these weapons

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and who had access uh different levels

7:39

of access the status required to have

7:42

access and um uh how it was used in the

7:45

wars um different formations of the

7:48

soldiers like they had all these like

7:50

crazy formation structures like forming

7:53

the army like a lotus forming the army

7:55

like a um you know there something

7:58

called a chakra vuha like a like

8:00

literally like it has to have concentric

8:02

circles. So you cannot like actually get

8:04

into the innermost circle without going

8:06

through the outer circles and then you

8:08

can get killed by each of the flanks

8:10

whenever you're trying to enter in. And

8:12

the secret of how to actually break into

8:14

these vuhas, vuhas means formations,

8:17

u was only known to a few people. And um

8:21

it it's it's it's it's incredible like

8:23

you could say, okay, like somebody had

8:25

to be extremely um skillful to have that

8:28

sort of like visualizations and

8:31

imaginations of describing a story like

8:33

that. And and obviously like Tl Keen has

8:35

done an amazing job with a lot of the

8:36

rings, you know, and creating so much

8:38

detail at the same time like a lot of it

8:41

actually coming through in real life in

8:42

some form. Again, not exactly the same

8:46

weapons but similar style makes you

8:48

wonder was there actually something

8:50

around then and uh people have tried

8:52

excavations in all these areas. There's

8:54

like two main areas in the Mahabarat.

8:56

how Singapore was the name of the

8:58

kingdom and people have done excavations

9:00

around there and have like found some

9:03

artifacts that might date back to those

9:05

years. But uh there are also some

9:07

details that are described in the epics

9:09

that don't quite align with reality. For

9:11

example, all the men, all the main

9:14

warriors in in that era were described

9:18

as like very tall, very big um 7 8 ft,

9:22

whatever, you know, I don't even know

9:24

exact numbers, but um but um his studies

9:30

by archaeologists also say that people

9:32

who lived in those years in in those

9:34

regions were probably not more than 6 ft

9:36

tall. So it's it's not clear exactly

9:39

like what happened, what was correct,

9:41

what was not correct. And you know, we

9:42

just have to keep probing more. But I

9:45

find the idea fascinating to think of

9:46

like what could have existed in sacred

9:48

texts that was only partially

9:52

communicated to the next generation and

9:53

having a lot of like reinterpretations.

9:56

Another thing that is very interesting

9:58

to think about is Vic math. So um the

10:02

basically Vic math is like a branch of

10:04

mathematics that you know some people in

10:07

India are grown up learning like I I I

10:09

read it myself too and uh some people

10:11

actually practice it just to be sharper

10:14

at mental math for doing their exams

10:16

like GMAT and things like that GRE and

10:20

um um it has like a line in the Vedas

10:24

that says oh like one from the last

10:26

digit two from the first digit whatever

10:28

you know so many different ways of

10:29

multly multiplying two different numbers

10:31

like 97 * 96. Oh, like subtract the last

10:34

two digits, put it in the right,

10:35

multiply the first digits, put it in the

10:36

left. That's that's the result. And um

10:40

then you you wonder like, oh wait, the

10:42

Rigveda is so old. It's as old as it's

10:44

is the oldest sacred text out there. How

10:47

is it describing computation?

10:49

That feels

10:51

>> right,

10:51

>> very unreal. Like do they actually know

10:54

or understand advanced forms of

10:56

computation

10:58

even back in those days? And um

11:00

>> and how old is rig beta?

11:02

>> Um I don't exactly know how old it is.

11:06

>> Why don't we put that in perplexity?

11:08

>> Yeah, let's do that.

11:09

>> Let's find out.

11:10

>> Yeah.

11:12

>> Yeah, it is technically the oldest

11:16

sacred text out there.

11:19

>> And so what's interesting is I wonder

11:23

how old the stories were by the time

11:26

they were written down. like how much of

11:28

it is relayed person to person

11:32

for years and years just like the Bible

11:34

before it's ever actually written down.

11:36

Scholars usually date the composition of

11:38

the Rigveda to about 1500 to,200 B.CE.

11:42

So its oldest layer is roughly 3,200

11:45

3,700 years old today.

11:48

Like I if there really was like every uh

11:53

ancient culture has a story of a flood.

11:56

every everyone they all have an

11:57

apocalyptic

11:58

>> marbar had the same thing

12:00

>> was it

12:00

>> Marbarat had the same thing where there

12:02

was a big like almost like a tsunami

12:05

like thing I don't exactly know what it

12:06

was called but that was the collapse of

12:09

Lord Krishna's kingdom Daraka after the

12:12

war a lot of people died but some people

12:13

survived and even those who survived got

12:16

wiped out by a calamity or or like some

12:19

kind of like a um fight among themselves

12:22

and um most of the people who

12:24

participated in that era actually died.

12:26

>> Here it is. The primordial, how do you

12:29

say it? Manu.

12:30

>> Yeah,

12:30

>> Manu flood. Classic Hindu great flood

12:32

myth where the righteous king Manu is

12:34

warned by a divine fish about an

12:37

imminent doge that will destroy

12:39

humanity.

12:41

He builds a boat, loads it with his

12:43

family. It's like knowing the ark. It's

12:46

the same thing with seeds and animals.

12:49

ties it to the horn of the god in fish

12:52

form which towes the boat to safety

12:54

until the waters recede and the world is

12:56

repopulated.

12:57

>> They all have the same story. Yeah.

13:00

That's what's really crazy.

13:01

>> There is a there is a concept in um

13:04

Hindu uh philosophy called the yugas.

13:07

>> Mhm.

13:08

>> I'm reading a book about it right now.

13:09

>> Yeah. Yeah. So uh there's like different

13:12

yugas and yugas are like thousands of

13:13

years and the concept is that the yugas

13:16

keep cycling around and so like uh we

13:19

are in the kal yuga right now and before

13:22

that was a dwara yuga that's when most

13:24

of mahabharat happened and before that

13:25

there was a traa where the ramayan

13:27

happened and before that there was

13:29

another yuga.

13:30

>> What is next after kal yuga?

13:32

>> It no there is nothing next after

13:34

kaluga. It goes back to the first one. I

13:36

forget the name of the first yuga

13:38

>> because the what the interpretation that

13:39

I'm reading is that we're not in Kalyuga

13:41

anymore and that Kalyuga ended in the

13:44

1900s and Dwaper Yuga started then.

13:46

>> No, no, we are in Kaluga right now.

13:48

>> 100%.

13:49

>> So why do people have different

13:50

interpretations? Like there is there is

13:52

that true? Yeah, there's like a guru

13:54

interpretation. There's like one

13:56

specific guru I see

13:58

>> that has this interpretation that

14:00

Kaliuga ended in the 1900s. Okay.

14:03

>> And that we're moving on. Interesting.

14:06

>> Yeah. But I don't know who's right

14:07

because it's it's an enormous cycle,

14:09

right? The cycles of humanity.

14:10

>> Yeah. Thousands of years. Thousands of

14:12

years. And uh

14:14

>> so

14:14

>> yeah. So these are the four yugas. Um

14:18

and um

14:22

>> so why do people have different

14:24

interpretations? What? Let me tell you

14:26

the book I'm reading.

14:27

>> Yeah.

14:29

>> Uh

14:31

see if this book is discredited. Young

14:34

Jamie, it is um

14:38

it's by a guy named uh David uh

14:42

Steinowitz

14:46

Stein

14:48

Steinmets. David Steinmets and the book

14:50

is called the Yugas. Interesting.

14:52

>> Yeah. I mean the the problem is when

14:55

someone's got their own interpretation

14:56

or some guru's interpretation, it

14:59

doesn't totally align. It's hard to know

15:02

who's right and who's wrong.

15:03

>> Yeah.

15:03

>> Keys understanding our hidden past,

15:05

emerging energy, age, and enlightened

15:07

future.

15:10

>> Yeah. So that go back up to that again.

15:13

So this is in the description. See what

15:15

it says that where it says in 1894 an

15:19

Indian sage gave us an explanation not

15:21

only for our hidden past but for the

15:23

trends of today and for future

15:25

enlightenment. So there's like one guy's

15:27

interpretation that this guy is going

15:30

off of.

15:31

>> I guess the difference might be that um

15:33

he thinks the yuga cycle is 24,000 years

15:35

whereas I think it's probably much

15:37

longer than that.

15:39

>> Yeah.

15:39

>> Um

15:40

>> four yugas together is 4,320,000

15:45

years.

15:46

>> You know what's really nutty?

15:47

>> Yeah. One of the really nutty things is

15:50

um both in the ancient Sumerian texts

15:54

and in some of the ancient Egyptian

15:57

texts, there's depictions before the

16:00

flood of people who reigned for

16:02

thousands of years as kings.

16:05

>> Yeah.

16:05

>> And it's common. It's not It's And it's

16:08

also they're referenced multiple times

16:10

in different scripts that are from

16:12

different parts of uh what was Sumera at

16:15

the time. Yeah,

16:15

>> it it's really weird because they take

16:18

it as established history once it gets

16:20

to a certain age once they get into like

16:23

whatever the age is where they can

16:25

verify that this person was the king for

16:26

a certain period of time. But it's all

16:28

in the same text as people that reigned

16:31

for 6,000 years.

16:33

>> Yeah.

16:33

>> It's it's really one just wipes out the

16:36

whole thing.

16:36

>> Yeah. And um I mean this is also

16:39

somewhat like tangentially related to um

16:43

um the firmy paradox

16:46

>> you know like if if you assume all these

16:48

things are happening on earth itself

16:50

that entire civilizations are getting

16:51

wiped out

16:53

>> um you and and like we always wonder you

16:56

you've explored this topic the most um

16:58

and um where are the aliens

17:01

>> right

17:01

>> and um there are different arguments

17:04

that like okay like the reason we I

17:06

haven't quite found that is because the

17:09

great filter exists and uh there is like

17:13

one entertaining theory that um I like

17:15

just for the sake of entertainment is um

17:19

almost all civilizations end up

17:20

advancing technologically a lot and um

17:23

either a calamity wipes them out or like

17:25

they build some misalign AGI and then

17:26

AGI wipes them out and um and because of

17:30

that um they never actually like end up

17:34

being visible to

17:36

Or the other theory is that like they're

17:39

like um we haven't quite built the

17:42

woyman probes to actually go find them.

17:45

And um both of them are plausible and um

17:49

it it you know the there's there's no

17:52

clear way to like know unless we

17:55

actually like send out enough probes.

17:58

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18:55

There's a bunch of possibilities. I mean

18:57

there's almost too many to count but

18:58

there's the possibility that they are

19:00

observing and that they don't want to

19:02

interfere and that we are on some sort

19:04

of a evolutionary cycle cycle of

19:07

cultural evolution civilization

19:09

evolution.

19:09

>> Yeah.

19:10

>> And one of the things about this the the

19:12

crazy ages that comes from the Samrian

19:14

text and from um the ancient uh the

19:18

hieroglyphs that depict the uh zeppet uh

19:21

how do you say it? Zepetti. No.

19:25

How am I saying that? What is that text

19:27

that ancient uh remember we talked about

19:29

it with Zahias and he denied its

19:32

existence?

19:35

Zepte, is that it? Either way, you're

19:38

dealing with these kings that reign for

19:40

thousands and thousands of years. Well,

19:42

you know, David Sinclair is in the

19:44

middle of this research now that's

19:46

they're working on life extension drugs

19:48

like that are actionable.

19:50

>> Yeah.

19:51

>> Yeah. That's it. Zepte.

19:52

>> Yeah, I've heard of that.

19:53

>> Um, so these, but this is what's so

19:55

weird. If they look at hieroglyphs, they

19:58

get to a certain point and they're like,

20:00

"Oh, Kufu, he was real. This guy was

20:02

real. All these people were real."

20:03

>> Yeah.

20:03

>> But then they get back to these guys

20:05

that reigned for thousands of years and

20:07

they go, "Oh, that was horshit."

20:09

>> But but why is it that all these people

20:12

have these stories that align with this

20:14

timeline that's pre flood?

20:16

>> It's all like the same story. Yeah. And

20:18

then if you're talking about

20:21

these ancient Hindu scriptures that are

20:23

discussing technology that seems

20:26

remarkably similar to technology that we

20:28

have today.

20:28

>> Yeah. The manas or flying cars basically

20:31

>> and probably what we're going to have

20:33

100 years from now or whatever it is or

20:35

or we could have gone that way in the

20:37

past.

20:37

>> And it's very entertaining to think of

20:39

like let's say something happens to us,

20:40

right? I don't want anything to happen

20:42

to us, but let's say something happens

20:43

to us. Would people really believe you

20:45

were like launching reusable rockets,

20:47

>> right? Or making FaceTime calls to

20:51

people in Australia?

20:52

>> Yeah.

20:52

>> Yeah. Like even fundamental things like

20:54

all we're doing today.

20:56

>> Um I think it's all like incredible.

20:58

Like there's there's a lot of things

21:00

that could be just technological ideas

21:02

or maybe people actually had it and the

21:04

knowledge of it was lost and it's not

21:07

been documented. It's not been passed

21:08

along and so we are skeptical if they

21:10

ever had it.

21:11

>> Yes. And so we end up reinventing it in

21:13

different forms again and again again

21:14

and we keep cycling through this

21:15

process.

21:16

>> Well, it also could be that this is the

21:18

natural progression of human curiosity.

21:21

The human curiosity and ingenuity always

21:23

moves into these very particular ways

21:25

like what's the best way to defeat my

21:27

enemies. Yeah. If we're always going to

21:28

be territorial primates, we're always

21:31

going to want to defeat our enemies.

21:32

We're always going to protect ourselves

21:34

from being invaded. So we're going to

21:35

make better in and just with

21:37

technological innovation, it just goes

21:39

down the same path. Oh, we figure out

21:40

bullets. Oh, we figure out nuclear

21:42

bombs. Well, we figure out well, we

21:44

don't even have to use an actual plane.

21:45

We can use an autonomous drone and that

21:47

delivers it. And then scale upwards and

21:50

onwards and AI and and then also life

21:53

extension. So, if these people were able

21:55

to make the pyramids like

21:58

you know there there's a lot of

22:01

speculation as to the timeline of the

22:03

pyramids, but let's just say they really

22:06

built it 2,500 BC. Let's just say back

22:08

then. What the were they using?

22:11

Like what were you What did you do? How

22:13

did you get these stones down from the

22:15

mountains that were 500 miles away?

22:16

>> How about this one?

22:17

>> How about that one? Yeah, we were going

22:18

to get to that for sure. There's a ton.

22:20

No, thanks. It's good to good as any.

22:22

How about these temples that they find

22:25

in India that are carved entirely out of

22:29

one piece of stone?

22:31

What did you do? How did you do that?

22:34

How long ago did this happen? How many

22:36

of them were buried and then they had to

22:38

uncover them and then like figure out

22:41

like what is this? Who made it? There's

22:44

no timeline. No one really knows.

22:46

There's no evidence of tools that were

22:48

capable of doing this kind of work back

22:51

then. And they're huge and beautiful and

22:54

perfect. And they have like acoustic

22:57

properties and the geometry is

23:00

fantastic. Yeah.

23:02

>> It's nuts, man.

23:03

>> It's not just that. All of these temples

23:04

were actually just built uh not just

23:08

they were specifically the locations for

23:10

them were picked out so that you get the

23:12

right uh seismic vibrations over there

23:15

in terms of like uh proximity to the

23:18

ocean, the gravitational waves from the

23:21

sun and the moon. People actually made

23:24

that level like look at this man.

23:27

Imagine the undertaking of carving that

23:31

temple out of the side of a

23:34

giant piece of rock.

23:37

>> Yeah.

23:37

>> You screw up one thing and it's over.

23:40

>> There's no simulations. You just have to

23:42

like build it.

23:43

>> Well, what did they have? This is the

23:45

question. Like imagine today if we had

23:49

to do this. Look, it's possible. This is

23:51

a possible endeavor. It can be done.

23:53

>> Yeah. But imagine what kind of

23:55

technology would we we have to need to

23:58

map it out to make sure that it was all

24:00

precise that it all align. I mean it's

24:02

precise within like millimeters from

24:06

point to point and everything is done

24:09

out of one piece of stone. Like what did

24:12

they do? Was it chisels? Did you do that

24:14

with chisels? That's crazy. How many

24:16

times you have to sharpen your

24:18

chisel? That's nuts. Or do you have

24:21

something completely different? Because

24:23

some of the more intricate ones, see if

24:24

you can find these. Some of the crazy

24:27

ones inside these temples, there's

24:29

sculptures that are three-dimensional

24:31

and they're carved like inside of the

24:34

sculpture. So, there's like an outer

24:36

area and then there's these all these

24:38

openings and then inside it's highly

24:40

detailed. Like, how'd you even reach in

24:43

there?

24:44

>> It just says they use chisels and

24:45

hammers and I don't think that's

24:46

possible.

24:48

and careful geometric planning planning.

24:51

>> People trying to do that. They see like

24:53

this is how much work someone could do

24:55

in like 12 hours with a a hammer and

24:57

they get nowhere, let alone like perfect

25:01

and looking good.

25:02

>> Yeah, it's nuts, man. And there's a lot

25:04

of evidence of stuff like that all over

25:06

the world, which is really weird. You

25:09

have the stuff in Peru like Saki Huan

25:12

when you look at these stones and it

25:13

looks like they're melted into place and

25:15

they're 900 tons. Like what did you do?

25:19

>> Yeah. How did you even get it up there?

25:21

>> How'd you where'd they get it? How'd you

25:22

get it there? How'd you align it

25:24

perfectly? Built in only 18 years. How

25:26

do they know that?

25:28

>> How do they know that? Cuz it's uh

25:30

attributed to one king.

25:32

>> Yeah.

25:32

>> So, King Krishna the 1 756 to 773

25:37

CE.

25:39

Maybe. I mean, how do you know though?

25:41

>> Yeah. They said the archaeologist said

25:43

it would have they calculated it would

25:44

take them 100 years to do it.

25:47

Yeah.

25:47

>> Yeah. I mean, this is where like, you

25:49

know,

25:49

>> I don't know.

25:49

>> Different historian accounts are all

25:51

like muddled up, you know.

25:52

>> Uhhuh. Well, it's a real problem.

25:54

History is a real problem.

25:55

>> But yeah, it goes back to like the thing

25:57

you were saying, right? You know, what

25:58

is one thing that's common across all

26:00

these different ages is human curiosity.

26:03

So, I mean, that's something that, you

26:05

know, I would love to get your take on

26:06

this. Um like I've been toying with this

26:09

idea called a curiosity premium which is

26:14

the most effective people the most

26:16

successful people have always been the

26:17

most curious people the ones who have

26:19

been good at asking the best questions

26:21

and they tend to do better in every

26:23

aspect of their life and uh you're

26:25

you're a good example of that. So that's

26:27

why I would love to get your take on

26:28

this. And the reason I believe that is

26:31

because um long-term people who

26:34

continuously ask questions tend to do

26:37

better. They make more money. They have

26:39

a higher quality of life. They're happy.

26:42

They have more compounding

26:43

relationships. People find them more

26:45

interesting. And so they compound their

26:46

relationships over time. And so uh

26:49

naturally they end up succeeding. But

26:52

their spirit of inquiry, their intrinsic

26:55

curiosity doesn't actually stop once

26:58

they succeed. It only they just

27:00

channelize it even more. And so that's

27:02

why it keeps compounding. And I would

27:05

argue that like it's the only quality,

27:06

it's the only like quality that makes us

27:09

really human, you know, in this world

27:11

where

27:12

>> we can seek a lot of information, get

27:14

information way faster than ever before.

27:17

It feels like that's that one universal

27:19

human quality that's existed since

27:21

ancient time since the oldest text. Like

27:24

in fact in in the Riga

27:27

um you're explicitly encouraged to seek

27:30

wisdom more than wealth. And it's not

27:32

just an idea specific to Hinduism. That

27:34

specific idea exists in the Bible. It

27:36

exists in the Quran. Exists in the

27:37

Torah. It's not that seeking wealth is

27:40

admonished by religious texts. It's

27:42

actually that it's more important to

27:44

seek wisdom. And um you know like you

27:47

can that why I said you're a good

27:48

example of that is like sure you have a

27:51

very very large podcast but the way

27:53

you're running it is like you're just

27:55

curious about a lot of things and asking

27:56

a lot of questions and I think that's

27:58

that one quality that's very important.

28:00

So um and I feel like it's the oldest

28:04

thing is the only thing that we've known

28:05

since ancient time being curious.

28:08

>> Well I I I think it's stimulating to

28:10

people and genuine curiosity is

28:12

stimulating to other people. when when

28:14

someone is genuinely curious about

28:16

something, I become curious about it. I

28:17

think it's contagious.

28:19

>> And I think that it's it's also an

28:21

authentic quality. And I think there's

28:24

there's something about really wanting

28:26

to know something and being interested

28:28

in something. And if you're curious,

28:31

generally, you're going to ask more

28:32

questions about something so you have a

28:34

deeper understanding of it. So if you're

28:35

trying to do whatever you're trying to

28:37

do, a sport, a game, you you'll probably

28:39

get better at it because you're more

28:41

curious because instead of just assuming

28:43

things, you'll ask more questions.

28:45

You'll reexamine things. It's genu it's

28:48

it's one of the most important human

28:49

qualities. And to me, it's one of the

28:50

most attractive human qualities. It's

28:52

always been. When I meet curious people,

28:54

I'm always interested. I'm always like

28:56

like, "Tell me what you're curious

28:57

about." And I'll tell you what I'm

28:58

curious about. Let's talk. You know,

29:00

it's it's um and this podcast started

29:03

out genuinely because of well, it was a

29:05

lot of just talking with friends,

29:07

>> but it also led into like one of my very

29:10

first guests, actual guests, was Graham

29:12

Hancock.

29:13

>> Mhm.

29:14

>> And it's just cuz I was curious because

29:15

I had read Fingerprints of the Gods and

29:17

I'd seen him talk. I'd seen speeches and

29:19

I'm like, I want to know like what do

29:20

you know? What do you think's going on?

29:23

And uh he's another guy incredibly

29:26

curious and absolutely fascinated with

29:29

his his takes on ancient history. He has

29:32

been talking about this subject a long

29:36

time. And when he first when he first

29:39

wrote Fingerprints of the gods, I think

29:41

that came out in like

29:43

I want to say it was like 97 or 98 or

29:46

something like that. And I remember

29:47

reading it and so many of my friends,

29:49

you know, educated friends like this is

29:51

horshit. Why are you paying attention to

29:52

this? More and more and more as time

29:55

goes on, it's been proven that he's

29:57

correct. The timelines shifted back and

29:59

from the publication of that book, the

30:01

discovery of Gobecletepe and the

30:03

surrounding area,

30:05

>> like it's like, okay, now we realize,

30:07

well, there was some crazy going on

30:09

at the very least 11,000 years ago. So,

30:12

we pushed civilization back 5,000 years.

30:15

>> So, like, and this is just what we found

30:17

now. And we keep finding things. Keep

30:20

digging. Keep looking. And then you see

30:22

the stuff that they're finding

30:23

underneath the pyramid with this radio

30:25

tomography where they're looking under

30:26

the pyramid that it seems that there's

30:28

structures under the py. You've seen

30:30

that stuff.

30:31

>> I haven't seen that.

30:32

>> I had the scientist that's involved in

30:34

it. He's an Italian guy, Filipo Bondi,

30:37

and he came on the podcast. Wonderful

30:38

accent. Almost as good as yours.

30:40

>> It was uh amazing. uh but he's

30:42

describing the use of this stuff and

30:44

that they've used it successfully on

30:47

known areas in uh pyramids and other

30:51

structures and they can det in for in

30:54

fact

30:54

>> they um there's a in Italy there is a uh

30:58

particle collider that is underneath a

31:00

mountain

31:01

>> and using this technology which is

31:03

satellite based technology they get an

31:04

accurate description of this particle

31:08

collider that's I think it's 1,200

31:11

meters underground. Like how how far is

31:14

that thing underground?

31:16

We'll find out. But it's like deep under

31:19

stone. And they find that they they can

31:22

get an accurate like they can actually

31:23

give you the dimensions of this particle

31:25

collider. They have like an image of it.

31:27

And this same technology is showing that

31:31

there's these columns underneath the

31:34

pyramid in various places that are 20 m

31:38

wide and they have coils around them.

31:41

They don't know what the hell they are.

31:43

And they the whole structure of this

31:45

thing, it's not small. It goes almost a

31:47

kilometer into the ground. There's like

31:49

this enormous like bottom of it. And it

31:52

seems like it's something that's

31:54

constructed. And so they're like, "Okay,

31:56

well, the pyramid is crazy. It's crazy

31:59

enough, but if there's something

32:00

underneath it that's a man-made or

32:04

someone made it that's a kilometer deep

32:06

into the ground, like what the are

32:08

we even talking about?" Like, who made

32:10

this? What What did they have?

32:13

>> 1.2 km in

32:15

>> 1.2 kilometers into the mountain.

32:19

>> That's nuts. It's a half a mile

32:22

in it plus into the mountain.

32:24

>> And this thing can see through all that

32:26

and get this accurate depiction of this

32:29

particle collider. And it's showing with

32:32

multiple scans, not just one, multiple

32:34

scans and different technology, the same

32:36

exact images, the same exact structures

32:39

underneath this immense

32:42

2,300,000

32:45

stone structure that almost perfectly

32:47

aligns to true north, south, east, and

32:48

west. Like what? What was going on?

32:51

Don't tell me police. Don't tell me

32:54

copper tools. Like what the was

32:55

going on? Something crazy. And I have a

32:59

feeling our simplistic explanation of it

33:01

is just doing no one any justice. It's

33:04

doing no service to history. It's doing

33:06

no service to our understanding. They've

33:08

got to be a little bit more open in the

33:10

fact that they are perplexed.

33:12

>> And not just perplexed by stuff like

33:14

this. This is a 3D print of an actual

33:17

vase that exists in Egypt that they

33:20

found that is they found it in tombs of

33:23

the old kingdom. This thing was somehow

33:26

another it's made with diorite. So it's

33:28

incredibly hard stone and made to like a

33:31

thousandth of a human hair in and it's

33:35

Yeah. like crazy dimensions

33:38

>> like the way the the precision of it and

33:41

wasn't turned on a lathe because it has

33:43

handles.

33:44

>> Yeah.

33:44

>> So you look at the handles on the side.

33:45

Well, you can't carve the and those are

33:47

perfect, too. Like the alignment of

33:49

everything and it's like you just look

33:51

at it. Oh, it's a vase. No big deal. But

33:53

no, it's kind of crazy. Like how

33:56

did they cut that out? There's also

33:58

these there's all these core marks in

34:02

some of the stones that they find in

34:03

Egypt and they've analyzed the amount of

34:06

revolutions per minute that you would

34:08

have to go through to be able to cut

34:10

through something and leave these lines

34:12

and not defies explanation. Like what is

34:15

this? This is crazy. This is not sand

34:18

and copper and just rubbing things. No,

34:20

this is some insane technology that we

34:23

don't understand. There's scoop marks

34:26

out of the bottoms of some of these

34:27

stones. It's like what? What the is

34:30

this? How'd you scoop rock? Like what?

34:32

It looks like ice cream. Like they just

34:34

went like what are they doing there?

34:37

There's so many questions.

34:39

>> What tools did do they even have to do

34:41

all these things?

34:42

>> They had copper. I mean there's there's

34:43

some evidence that they had some iron

34:46

and then I think Tuton Common had a

34:48

dagger that was actually made from

34:49

meteorite which is interesting. you

34:51

know, like when they could find

34:53

meteorites and make things out of them,

34:55

it was very valuable, obviously. But the

34:58

just the sheer volume of work that they

35:02

did there, it's you if like you look at

35:05

the temple in man, you look at all the

35:07

the three major pyramids, you look at

35:10

all the different temples and all the

35:12

construction and the older you go, the

35:14

deeper into the sand they go, the more

35:16

complex these things are, which is even

35:18

weirder. Yeah.

35:19

>> So it seems like civilization after

35:20

civilization just they would there was

35:22

probably a rise and fall with their

35:25

technology as well.

35:26

>> Absolutely. I think it's it's it's just

35:28

incredible that none of this knowledge

35:30

was properly documented ever. And uh

35:33

it's a whole like line of work to just

35:35

go understand like how to even rebuild

35:37

these things leave alone how did they

35:39

build it.

35:40

>> Well think about what we're doing right

35:42

so all of our knowledge is essentially

35:44

stored on hard drives and paper. Mhm.

35:46

>> Those are the the two things that are

35:48

going to deteriorate the quickest.

35:51

>> Maybe we should like take a dump of the

35:53

internet and

35:54

>> put it on a rock,

35:55

>> go preserve it somewhere so that Yeah.

35:58

>> even if our our civilization is wiped

36:00

out and all the data centers are like

36:01

gone or whatever,

36:02

>> right?

36:03

>> Whoever comes next can go figure it out.

36:06

Well, I mean, then you've got to always

36:08

assume that even if they found a hard

36:10

drive that they would like, how long

36:12

would it take for them to backineer what

36:15

we did and figure out what these ones

36:17

and zeros actually mean?

36:19

>> Yeah.

36:20

>> That what is which is one of the most

36:22

bizarre and fantastic accomplishments of

36:25

modern civilization is that like

36:28

>> this is a terabyte.

36:30

>> Yeah.

36:30

>> Which is nuts.

36:31

>> Yeah.

36:32

>> Like I don't know what your first

36:33

computer had. I don't remember.

36:36

Definitely not not even a gigabyte

36:38

probably.

36:38

>> No, like a few hundred megabytes was

36:41

your hard drive.

36:42

>> Yeah.

36:43

>> Yeah. I mean, I remember when they first

36:45

came out with gigabytes, I was like,

36:46

"This is nuts."

36:47

>> Yeah. You remember like when Gmail

36:49

launched and gave everybody like free

36:51

email storage, unlimited email storage,

36:53

and the bottom sliding bar would just

36:55

keep increasing in terms of the total

36:57

allowed size.

36:58

>> Yeah.

36:58

>> And that was nuts to me. And Yeah. And

37:01

and uh I think yeah we take it for

37:03

granted that we have like infinite RAM

37:05

and infinite hard disks and nobody has

37:07

to worry about like you know you back in

37:09

those days you would worry about like

37:11

taking too many photos on your phone.

37:12

>> Right.

37:13

>> Right. And then you have to go delete

37:14

all the old ones or bad ones.

37:16

>> Yeah. You'd run out of storage on your

37:18

phone.

37:18

>> Yeah. And then you would have to buy

37:19

like an external hard drive to keep

37:21

storing things.

37:22

>> Keep transferring stuff from your phone

37:24

to the hard disk.

37:25

>> I remember the old Android phones. You

37:27

get a SD card. You could slip one of

37:29

those in there and you could store

37:30

images on that so you could

37:33

>> save space.

37:34

>> Yeah.

37:34

>> And all that stuff is so vulnerable.

37:37

It's so vulnerable. And again, if a

37:40

completely alien society had to come

37:43

down and find our hard drives and they

37:46

went a totally different path of

37:48

technology. They'd have to backineer,

37:50

reverse engineer everything that we did,

37:52

try to figure out, you know, what what

37:54

what are we using? What operating

37:56

system? How's the operating system work?

37:58

Is it Unix? Is it Linux? Is it like what

38:00

is it? How do they do it? It would be a

38:02

nightmare.

38:03

>> They would need an advanced AI to like

38:05

figure it all out for them,

38:06

>> right?

38:07

>> Yeah.

38:08

>> Yeah. And so, uh, that's just if the

38:10

hard drive survive, right? So, if

38:12

there's some massive flood, cataclysm,

38:15

whatever, some some horrific thing that

38:18

damages all of our electronics, which is

38:20

totally possible,

38:21

>> you know, just some solar flare, some

38:23

intense,

38:24

>> you know,

38:24

>> or just just just another lab leak,

38:28

>> right? Yeah. Just time, a lab leak in

38:31

time.

38:31

>> Yeah.

38:32

>> Yeah.

38:33

>> It's nuts. And it we could go back to

38:36

zero real quick and we would basically

38:39

be like preppers and hunt. hard to

38:41

reverse engineer everything again.

38:42

>> It would be almost impossible.

38:44

>> Which is why I'm really fascinated by

38:47

the flood the post flood timeline

38:49

because if these people like Graham

38:51

Hancock and a lot of these other folks

38:53

that have speculated that there was

38:55

probably a very advanced civilization

38:57

that went in a completely different

38:58

direction many thousands of years ago.

39:01

If you look at like the emergence of

39:04

like Sumere and you know Mesopotamia and

39:07

that area which a lot of people

39:08

attribute to be the earliest known

39:10

civilization that's around 5,000 plus

39:14

6,000 years ago rightly.

39:17

>> So the flood's like 11,000 years ago

39:20

>> plus. So you're looking at like 5,000

39:23

years of what?

39:25

>> That's not even that long in the grand

39:26

scheme of things.

39:27

>> No, not to the earth but for people

39:30

pretty long. Like think of how

39:31

long it took us to get our

39:32

together. Yeah.

39:33

>> It took thousands and thousands and

39:35

thousands of years of people probably

39:37

being monsters. Just being the the worst

39:41

of the worst. And that that's probably

39:43

the only way they survived. There's

39:44

probably a lot of cannibalism. There's a

39:46

lot of murder.

39:47

>> There was a lot of like horrific

39:49

going on for 5,000 years until people

39:51

slowly but surely figured out

39:53

agriculture again. Yeah.

39:54

>> Started building walls. Everybody

39:56

relaxed a little. got some solid weapons

39:59

to keep people away so you could work on

40:01

math. And then next thing you know,

40:03

civilization emerges again and it goes

40:05

right, you know, goes right back onto

40:07

the cycle. And then you start reading in

40:09

the the Rig Va about stuff that happened

40:12

thousands of years. You go, wait, what

40:13

the is this? Like what happened?

40:15

>> Yeah.

40:15

>> And that's my belief. Yeah. I think

40:19

there was something going on on Earth

40:21

many many many thousands of years before

40:24

established beginnings of history that

40:27

was very bizarre and probably technology

40:29

that went in a completely different

40:31

direction than what we're doing now with

40:34

combustion engines and circuits and all

40:37

the different things that we use. They

40:38

probably figured out some other kind of

40:40

technology.

40:41

>> Exactly.

40:42

>> Yeah.

40:42

>> Which is totally possible. And it's it's

40:44

amazing like it's amazing to think of

40:46

like what if we could rediscover all of

40:48

that again. And

40:49

>> yes, well I would love to be able to I

40:51

would love to just have a w if I could

40:54

choose one window in time to go back to

40:57

see what it would look like. I would

40:59

100% pick ancient Egypt while they're

41:02

building.

41:02

>> Mhm. The pyramids.

41:03

>> Yeah.

41:04

>> Show me what the was going on.

41:06

>> Yeah.

41:07

>> There's just just put me in a big

41:08

hamster wheel. There's a big plastic

41:10

bubble where no one could see me. Just

41:12

let me violate space and time and exist

41:14

there for just a few minutes. Just let

41:16

me look. I think that would be the most

41:19

insane thing that you could see about

41:21

humans in human history.

41:23

>> Yeah.

41:23

>> I just I want to know what they knew,

41:25

what they had, what they used.

41:27

>> Look, this thing Petra is same time

41:29

period at least attributed to 7,000

41:32

roughly BC.

41:34

>> Jesus. And they, you know, how would you

41:38

do that?

41:38

>> How?

41:39

>> The details of all those car carvings is

41:42

just insane.

41:42

>> Insane.

41:43

>> Yeah.

41:43

>> And what in 7,000 BC? What are the

41:46

tools?

41:48

What the hell were you using? How did

41:50

you make a temple out of the side of a

41:52

mountain? Look at the size of

41:55

it, man. The size of those columns.

41:58

>> It would be hard to do anything like

42:00

this even today.

42:01

>> It would be incredibly difficult.

42:03

insanely time consuming.

42:05

>> Oh. Uh yeah, the Caliosa Temple, by the

42:08

way, I uh I don't have it up right now,

42:09

but the uh in 1650 or so, someone sent a

42:13

thousand people to try to destroy it,

42:14

and after three years of doing nothing,

42:16

they stopped. They barely made a dent on

42:18

a couple statues.

42:20

>> Yeah. A lot of times when invasions

42:22

happen in India, like

42:23

>> they tried really hard to it up and

42:25

couldn't.

42:26

>> Oh, wow.

42:26

>> That's crazy.

42:28

>> That's very robust.

42:33

That's a great way to describe it. It's

42:36

just there's so much of that stuff

42:38

that's so interesting because it's so

42:42

undeniable. It's so undeniable in its

42:45

scale. So undeniable in its complexity

42:48

and the the planning and the the the

42:50

understanding that you you had to have a

42:53

a deep knowledge of geometry, of

42:56

measurement, of you had to have accurate

42:58

Yes. everything. sturdiness like resist

43:02

like calamities like earthquakes. If you

43:04

had that floods, what tools are you

43:07

using?

43:07

>> Yeah.

43:08

>> Like how are you doing this?

43:09

>> Yeah.

43:10

>> How are you coordinating all these

43:12

people and getting them to do stuff? And

43:14

>> I mean sure conditions must have been

43:16

way harsher. Like I'm sure people didn't

43:18

really have a choice but to do these

43:19

things because back in those days like

43:21

the only way you could take care of your

43:24

food and clothing and shelter is like

43:26

you commit yourself as a labor laborer

43:28

to the state to the kingdom. But you

43:31

could also ask like how what gave them

43:33

the initiative or drive to go do these

43:36

things.

43:37

>> Yeah. Well, that description is perhaps

43:39

of a later time. We don't even really

43:41

know what civilization was like when

43:43

these were constructed.

43:44

>> Yeah. the the real the real problem is

43:47

the material science. The real problem

43:50

is like you there's a lot of things that

43:52

you have to have to make those things.

43:54

It's not as simple as a sculpture like

43:56

Michelangelo making a sculpture out of

43:59

something that's like fairly easy to

44:00

carve into as far as far as stone goes.

44:04

You know, this is the scale is imp it's

44:06

so undeniable

44:08

that like something something some piece

44:11

of our understanding is missing. Yeah.

44:14

Yeah. I mean it it it like looking at

44:17

all this like everyone should just be

44:19

like a lot more humble, right? Like like

44:21

we don't actually know that much like

44:23

the what we know is like so little like

44:25

like whatever like the same thing as

44:27

what Socrates said. What we know is very

44:29

very little.

44:31

>> And the only thing we we should all

44:33

strive to be is just be curious. And um

44:35

I think there's a lot of tendency for

44:37

people to like think like oh like we

44:39

have all this advanced technology we're

44:40

so amazing like look at us. And it's

44:43

like, wait, hold on. Like, you don't

44:45

even understand what happened thousands

44:46

of years ago. And uh there's so much out

44:49

there to just go and explore and learn

44:51

and like get better at understanding

44:53

more.

44:54

>> What is this place?

44:55

>> This is Yeah, this is unreal.

44:58

>> This is called the Ora Caves. Timeless

45:01

wonder carved in stone.

45:02

>> They're all I think it's all like kind

45:03

of the same area.

45:04

>> Yeah, it's it's the same Allora cave in

45:07

the Shiva Temple that you saw.

45:08

>> Look at that. My god. Look at this

45:11

stuff. It's insane.

45:15

And again, there's no steel back then.

45:18

>> It's actually really symmetrical. It

45:20

It's It's not even like uh in Can you go

45:24

back to the f the first one with with

45:25

the symmetrical top? Yeah.

45:27

>> Look at the symmetry at the top. This is

45:30

>> It's nuts.

45:31

>> It looks like that mall in uh New York

45:34

they made where the World Tra

45:37

>> Yeah. But way more robust.

45:41

I mean, how what what did what were you

45:44

they you this is the thing is like the

45:46

material science aspect of it.

45:48

>> Yeah.

45:49

>> It's like you don't have the ability to

45:51

do Look at that top one. Go to that top

45:53

one again. The one that you just had,

45:55

Jamie.

45:56

>> Yeah, that one.

45:57

>> Look at that's crazy, man. I mean, I am

46:02

just blown away when I see stuff like

46:04

that. My mind just starts racing and I

46:06

just think, how did you do this? Who who

46:10

was involved? How was it planned? How

46:12

was it so symmetrical? What were the

46:14

tools?

46:16

Like what were the tools, man? If you

46:18

don't have steel,

46:20

>> you don't have what are you using? How'd

46:23

you do that? I

46:23

>> mean, most of it is done with stone,

46:25

clearly, right? So,

46:26

>> I guess I guess I doubt it. I bet they

46:30

had something else. I bet they had

46:33

something else that over time eroded

46:35

just like metal would today. I mean, if

46:37

you left a shovel outside today

46:41

and you came back to that same spot 500

46:43

years from now, there's nothing. That

46:45

shovel's gone, right?

46:47

>> Yeah.

46:47

>> And you've got to assume that these many

46:50

thousand-year-old temples that were

46:52

carved out of a mountain,

46:54

whatever tools they used probably got

46:57

absorbed by the earth. And the only

46:58

thing that's remaining,

47:00

>> it's giving me a weird thought. Like

47:01

when they make a big building downtown

47:02

though, they only bring the crane in for

47:03

a temporary period of time. And there's

47:05

only so many cranes on the planet

47:07

currently, too. So,

47:08

>> Right.

47:09

>> True.

47:09

>> You take it and you move it, you go take

47:11

it to the next spot.

47:12

>> Yep. Yeah. True.

47:14

>> Yeah. I don't know.

47:14

>> Yeah. Especially something like this,

47:16

like if they had heavy equipment and

47:18

machinery and whatever the they

47:19

were using, they probably moved it and

47:21

then moved it out and then it probably

47:23

rotted away and now it's gone. If there

47:25

was machinery. If there wasn't, like

47:28

there must have been something else.

47:29

Some other kind of like some technology

47:32

that we haven't even imagined. Yeah.

47:37

>> But it's like their

47:39

their commitment to art too was so

47:43

fascinating cuz these aren't just

47:44

structures. They're incred.

47:46

>> Yeah. Intensely beautiful.

47:48

>> Intensely ornate.

47:50

>> Yeah.

47:50

>> So it's not it's not just that they

47:52

wanted to build like a functional

47:54

structure that good architecture. No,

47:57

it's this it's a fascinating artwork and

48:00

it's so intricate. There's so many

48:03

different features and so many different

48:05

images of of different people and beings

48:08

and animals and elephants. And

48:11

>> there's one more temple like you could

48:13

pull out like it's called the Tangar

48:14

temple.

48:15

>> Oh, I've seen that one too. Yeah. Yeah.

48:17

>> That was done more recently in the in

48:19

the age of the Cholas and um it's um

48:21

it's pretty incredible.

48:22

>> When did they do that one?

48:24

>> Um I don't know the exact number but

48:27

more recent than the other ones that you

48:28

saw.

48:29

>> All of them are nuts, man. And then

48:31

there's stuff like that all over the

48:32

world. Whoa.

48:35

>> This was done as a as a project by the

48:37

king um to to basically make a name for

48:40

himself.

48:41

>> Wow. That's incredible.

48:45

Is that multiple pe pieces of stone or

48:47

did he carve that whole thing out of

48:49

stone too?

48:50

>> Probably multiple pieces.

48:52

>> So that's actually like construction.

48:55

>> Yeah.

48:55

>> Not like removal.

48:58

The other ones are it's essentially a a

49:01

giant sculpture.

49:04

Wow, it's so pretty. Look how geometric

49:06

it is, too.

49:07

>> That's what amazes me. Like, they didn't

49:09

actually have all these simulations and

49:11

CAD tools and all these things,

49:13

>> right?

49:14

>> And uh

49:15

>> what year was this made, Jamie?

49:17

>> Does it say

49:19

it's just so incredible how much of this

49:22

stuff exists where it's really baffling?

49:24

Like I just found out recently that the

49:27

Aztecs didn't build those temples that

49:30

they found them.

49:31

>> Really?

49:32

>> Yeah. They found like the Tinoitlon.

49:34

They they call it the place where the

49:36

gods were born.

49:37

>> Mhm.

49:38

>> The Aztecs found it and uncovered it.

49:40

And then on the when uh was it Tano

49:44

Chitlan or uh Tioto which whichever one

49:48

it was on the consecration day when they

49:51

were done with like whatever they were

49:52

doing with it to celebrate they killed

49:55

somewhere between 20,000 and 80,000

49:58

people in 4 days.

50:01

>> Damn.

50:03

>> Not exactly the mindset of the type of

50:04

people that would construct something

50:05

like that,

50:06

>> you know. So those are the people that

50:08

found it and it might have been sitting

50:10

there for a thousand years and then they

50:12

came along and said, "Oh, this is cool.

50:14

Let's live here." Okay. Well, what was

50:16

the society that lived there before

50:19

them? And where are they and what

50:20

happened and how' they do this and why'

50:23

they do it and why did they have it

50:24

aligned with the constellations? Like

50:26

what were they doing? Yeah,

50:29

it's some some of the some of the

50:30

calculations are pretty pretty amazing,

50:32

like how they timed it, how they

50:35

positioned it, how they cared about

50:37

planetary positions and stuff like that.

50:40

Sure, like some of it could even be

50:41

pseudocience, but whatever. I think just

50:44

the level of like calculations they were

50:46

making back in those days without, you

50:48

know, powerful computers is just

50:50

outstanding.

50:51

>> It's just nuts and it doesn't make

50:53

sense. It's like okay they're making it

50:55

without powerful computers. So what are

50:57

they using?

50:58

>> I mean at one point the word computer

51:00

just meant a human

51:02

>> right

51:02

>> like human beings would be doing the

51:04

calculations. That was their only job

51:05

like to like multiply two numbers or

51:09

like to to make some astronomers were

51:12

actually the first mathematicians.

51:14

The term mathematician and astronomer

51:15

were used synonymously at one point.

51:17

>> Really?

51:18

>> Yeah.

51:20

>> Why is that? Why why most of the stars

51:23

and math?

51:24

>> Yeah. Because like studying the stars

51:26

involved making a lot of geometry

51:28

calculations and um um that was kind of

51:31

actually one of the first set of

51:33

mathematicians in India. People like

51:35

Arya Bata Bascara all these guys were

51:38

actually astronomers too. They were not

51:40

just mathematicians.

51:42

M

51:43

>> and um Arya was earlier to like like the

51:46

idea of using zeros and then um he had a

51:49

lot of like contributions in geometry

51:52

and he was doing all this like just

51:54

because he was interested in astronomy.

51:57

>> Isn't there evidence of Pythagore

52:01

theorem in ancient is it ancient

52:04

Samrian?

52:06

Is it

52:08

>> it's some anc something something that

52:11

predates Pythagoras.

52:13

>> Interesting. My my theory is that even

52:16

though it was not formulated as a

52:17

pythogan theorem like I'm sure people

52:19

had to understand concepts of sign ss

52:21

and cosiness and like you know whatever

52:24

is the right angle for the right incline

52:26

to get this right level of like geometry

52:28

you need to you needed to have some

52:30

implicit understanding of it to build

52:32

these kind of structures. There's no way

52:34

you could do it without that.

52:35

>> Yeah 100%. and and you have to have

52:37

incredible measurement tools like not

52:39

just the actual mathematics.

52:42

>> Okay. The oldest known evidence of

52:43

Pythagoran theorem dates from old

52:45

Babylonian clay tablets from about 1900

52:48

to600 B.CE roughly 1,000 years before

52:52

Pythagoras. Isn't that wild? like how

52:57

how Clay Tabots often cited uh used what

53:00

we now call the Pythagorean theorem to

53:03

complete to compute rather the di

53:05

diagonal of uh rectangles

53:08

and squares including an excellent

53:10

approximation. Look at this. This is

53:13

nuts, man. Vadic ritual text explicitly

53:17

states the rule equivalent I don't know

53:19

how to say that. What is that? A A B

53:21

square C= C^ square for the diagonal of

53:24

a rectangle that includes numerical

53:25

examples predating or roughly

53:27

contemporary with classical Greek

53:29

mathematics. So completely different

53:32

parts of the world.

53:33

>> Yeah.

53:33

>> And they're coming up with the same

53:34

stuff.

53:35

>> Exactly. Because they're all curious.

53:37

That's it.

53:38

>> Yeah. They're all curious and eventually

53:40

all curiosity leads to truth or some

53:43

form of it. I would argue that anything

53:45

anything that's of impact in the world

53:47

has only been done by curious people. In

53:49

hindsight, we label those people as

53:51

successful, as smart, or rich, but the

53:54

common trait across all of them has been

53:56

like curious.

53:59

>> Well, that's certainly a powerful trait.

54:02

And people that aren't curious are not

54:04

fun.

54:05

>> Yeah, they're not interesting. So,

54:07

because of that, they don't attract

54:09

other smarter, interesting people. and

54:11

therefore they won't be able to do

54:13

something very meaningful in the world.

54:15

>> So it's it's it's it's kind of like um

54:18

um it's less about and and it applies to

54:21

your personal relationships and personal

54:23

life too. It's not just about

54:25

professional success like you'll have a

54:27

more fulfilling life with your wife or

54:29

your kids if you're a more curious

54:30

person. You ask them more questions. You

54:33

you you take interest in them, right? So

54:35

that's that's the one quality everybody

54:37

wants in personal relationships is like

54:39

taking interest in them and like

54:41

actually understanding them better or

54:42

like being curious about common things

54:45

and um so it's not just that you know

54:48

being curious leads to success. It's

54:49

more that people around you want you to

54:51

be successful if you're curious because

54:54

um you will have more compounding and

54:56

fulfilling relationships.

54:58

>> I would agree with that. Yeah. I'd say

55:00

it's one of the more more important

55:02

qualities of human beings. I mean it's

55:04

led to everything that we have today.

55:06

All curiosity has led to all of our

55:08

architecture, math. Yeah. Everything.

55:10

Art, everything.

55:11

>> The transistor, like you know the story

55:13

of the transistor.

55:14

>> Yeah.

55:15

>> So Bell Labs was basically employing as

55:17

many like like history adjusted as many

55:20

telephone engineers back then as the

55:22

number of software engineers today. But

55:24

only three people cared enough to

55:26

question whether you should use these

55:28

really hot giant vacuum tubes for

55:30

amplifying telephone signals. So vacuum

55:33

tubes were very big, power hungry and uh

55:36

very hot and so they were not fall

55:39

tolerant and it's very expensive and so

55:41

three people questioned the need for

55:42

that and came up with the idea of the

55:44

transistor to to to amplify current and

55:48

that that was the Nobel Prize winning

55:50

discovery and not just that it was

55:52

useful to amplify telephone signals. It

55:55

basically led to the rise of modern

55:56

computing and we wouldn't have an iPhone

55:58

like this today if if not for those

56:00

three people. Do you know what the

56:02

tinfoil hat conspiracy theory about

56:03

transistors is?

56:04

>> No.

56:05

>> It that they are back engineered from

56:08

the Roswell crash along with fiber

56:11

optics.

56:12

>> Any more?

56:13

>> So, uh, we read this on the podcast.

56:15

Remember Jamie? There's the two

56:17

scientists that were attributed. There's

56:18

this one scientist that said they

56:20

weren't even remotely exceptional guys

56:22

and that they gave them the credit for

56:24

this so that they didn't have to reveal

56:26

the true nature of where this technology

56:29

came from.

56:30

>> I see. Interesting.

56:31

>> So again, tinfoil hat securely on our

56:35

heads. This is not something I believe.

56:37

>> Okay.

56:37

>> This is just something that's fun. Um

56:40

there's a few inventions that came out

56:43

of that time period roughly after 1947

56:47

>> that are weird and one of them is fiber

56:50

optics and one of them is a transistor

56:51

and these are supposedly attributed to

56:54

back engineering programs.

56:55

>> So the Roswell crash, I don't know if

56:57

you ever paid any attention to it. It's

57:00

a real weird one because the cover of

57:02

the Roswell Daily Record said that the

57:04

government has a crash disc that landed

57:07

in the desert. Bunch of witnesses, bunch

57:09

of people saw it.

57:11

>> It's also people that saw um supposedly

57:13

saw physical bodies of these creatures

57:16

and a supposedly uh

57:20

again, who knows what's true, but Truman

57:24

went to the site. He visited it and then

57:27

the planes, two separate planes were

57:29

flown to Wright Patterson Air Force base

57:32

uh which was uh I think it was just

57:33

right base back then. I don't think it

57:35

was right Patterson but they they flew

57:37

them out and the idea was this material

57:41

was so important they didn't want to

57:43

risk one plane crashing. So they flew it

57:46

in two different planes and that this

57:48

stuff has always been known to be stored

57:50

at Wright Patterson Air Force Base.

57:52

That's what everybody always talks

57:53

about. And then a lot of it was moved to

57:56

Bell Labs. And wow,

57:58

>> there was a company called the American

58:01

Computer Company. And back in the day,

58:03

the American Computer Company was just

58:05

like it was a consumer website where you

58:08

could go and say, "Oh, I need a Windows

58:10

computer that does this, that, and the

58:11

other thing." And you could just put in

58:13

whatever your specs were, and they would

58:14

build it for you. But they had a whole

58:16

section of their website dedicated to

58:19

Bell Labs and back engineered UFO

58:22

technology and all they talked about in

58:24

this one like whoever ran it was like a

58:26

cook. I don't Is that still

58:28

around

58:28

>> that website?

58:29

>> Yeah. American computer company. Is it

58:31

still around?

58:32

>> Interesting.

58:32

>> So this is like the 1990s I think. So

58:34

you're saying your your your theory I

58:36

mean not that you believe in it but your

58:38

theory is that uh the transistor was not

58:41

like invented it was known and it was

58:43

given to the

58:44

>> there's apparently a giant leap between

58:46

the first ideas of the transistor and

58:48

then what it what actually came about

58:50

and how much money had to be spent to

58:52

create it off of this leap. This was

58:55

this

58:57

>> assertion by these scientists that were

58:58

trying to examine this. The thing about

59:00

Bell Labs is there's a military base

59:04

right outside of Bell Labs and they say,

59:06

"Well, that military base is to guard

59:07

New York City." But New York City is

59:09

quite a flight away, but Bell Labs is

59:12

right there.

59:12

>> Yeah.

59:13

>> And they were working on some deep dark

59:16

at Bell Labs for sure because I've

59:18

had a bunch of people on that were

59:19

talking about uh remote viewing

59:21

exercises that they were doing out of

59:23

Bell Labs. You know, we've had a bunch

59:25

of people that came on and and talked

59:27

about various programs that were going

59:29

on that were like top secret programs

59:31

that were happening that were being run

59:32

through Bell Labs. Like there's some

59:34

weirdness to that place. Like real

59:36

weirdness.

59:37

>> Interesting.

59:37

>> Yeah. And it's fun. Yeah,

59:39

>> the idea that like

59:41

>> you know that

59:43

>> it it it definitely feels very

59:44

disconnected like okay like you were

59:46

using all these vacuum tubes um and then

59:50

suddenly you're like okay like what if

59:52

we just use semiconductors

59:54

okay that there's definitely a pretty

59:57

far drift from what you're doing

59:59

currently to what you're supposed to do

60:02

>> and um um and also the the the idea of

60:05

the first transistor and what ended up

60:07

being used in chips

60:09

the junction transistor are quite

60:11

different too. So they're like big leaps

60:13

in terms of what the core idea was. It's

60:15

not an incremental change. Um the way I

60:19

thought about it was like okay that's

60:20

like tens of years of work and that's

60:23

why they made a big change and so if you

60:25

actually looked into the individual

60:27

milestones they had maybe it would have

60:29

looked pretty different. But your um

60:31

conspiracy theory is pretty interesting.

60:33

Like

60:33

>> it's always fun.

60:34

>> Yeah. Um and and also there's just too

60:37

many stories of this and David Grush has

60:41

you know on oath said that they there

60:43

are back engineering programs and he was

60:45

read into these and that they've been

60:46

around for a long time but

60:48

>> this is the assertion of that movie the

60:50

age of disclosure that the real problem

60:52

is that they have misappropriated funds

60:54

and lied to Congress and so they come

60:56

out and tell you okay we do have this

60:58

program well guess what everybody goes

60:59

to jail because you guys are a bunch of

61:01

liars and uh you've been stealing money

61:03

and you've been doing whatever you want

61:05

to do with this money. I don't know like

61:07

how much how much oversight is there on

61:10

back engineering UFO programs, you know?

61:13

So, probably a lot of people get in

61:14

trouble. A lot of people go to jail. On

61:16

top of that, these things are all being

61:19

done by weapons manufacturers, right?

61:22

Like where are you going to bring them

61:24

to? Well, you're going to bring them to

61:25

Loheed Martin or you going to bring them

61:27

to, you know, Rocket Dine or it's going

61:29

to be someone that does that kind of

61:30

work. Yeah. You're not going to do it on

61:32

your It's not going to be like we'll do

61:33

it. No, you're going to have to bring it

61:35

to people that already make spaceships

61:36

or bring it to people that already make

61:38

jets.

61:38

>> Yeah.

61:39

>> And so they have a massive competitive

61:41

advantage over any other company that's

61:43

doing it. So then there's other

61:44

companies that also had contracts with

61:46

the United States government they can

61:47

sue. And so he lays out all the problems

61:50

with disclosure. And their assertion is

61:53

that the only what we need if we really

61:57

want to find out the truth is we're

61:58

going to need widespread amnesty for all

62:01

these people that were involved. Mhm.

62:03

>> My problem with that is that's what I

62:05

would say too. If I had been stealing

62:07

money for decades and decades, I'd be

62:09

like, I we need amnesty and I'll tell

62:12

you where all this stuff is. I'm like,

62:14

how do we know what this stuff is,

62:18

whether or not these are just top secret

62:20

military programs with advanced

62:21

propulsion technology that's unavailable

62:23

to the public and they're going to say

62:24

that is aliens and they backgineered

62:26

this and they did that. Like, they

62:28

clearly don't want to tell people. They

62:30

don't want people to know. I think a

62:32

large part of it is probably because

62:34

they could get in trouble. But I think

62:36

also a large part of it is because it's

62:38

fun to keep secrets from people.

62:39

>> Yeah.

62:40

>> Especially when you're the government.

62:41

Why tell them? those people.

62:43

>> Yeah.

62:43

them. They don't even know UFOs are

62:45

real.

62:46

>> Meanwhile, you know, we're going into a

62:48

bunker in the middle of the mountain and

62:49

we're remote viewing. You know, it's

62:53

it's probably there's probably a lot of

62:55

fun involved in having access to

62:57

information that most people would kill

62:58

for.

62:59

>> Yeah. I mean there's so much information

63:01

that um we just we just don't have

63:04

access to.

63:05

>> Which brings me to this question with it

63:09

seems like one of the things that's

63:10

happening with uh both with AI and with

63:13

technology in general is that you have

63:16

more and more access to information and

63:19

more and more answers to questions than

63:21

ever before.

63:21

>> Yeah.

63:23

>> At a certain point in time there's going

63:26

to be no bottleneck.

63:27

>> Yeah.

63:27

>> And we're going to know everything about

63:29

everything. So, how is anyone in

63:31

government going to keep a secret? How

63:33

is any corruption ever going to be

63:36

possible? Is at a certain point in time

63:39

all of it will get uncovered? Like, it's

63:40

much more difficult to commit murder now

63:42

with DNA evidence, right? Back in the

63:45

1800s, like I didn't see nothing. I

63:47

wasn't there. And then you're free.

63:49

Like, now they do your fingerprints.

63:52

Now, they get your DNA. Now, there's

63:53

flock cameras. There's like more and

63:56

more and more. It's harder to get away

63:58

with things. Yeah.

64:04

>> Ultimately, there's going to come a time

64:05

where there's so much data and so much

64:07

information and you could run all your

64:09

questions like there's an AI fact

64:12

checker for politicians now. Yeah.

64:13

>> So, while a politician is giving a

64:15

speech, you can run an AI fact checker

64:17

and in real time it will tell you

64:19

whether or not these people are full of

64:20

This it seems like the direction

64:22

is there's not going to be anybody full

64:24

of in the future because it's not

64:25

going to be possible.

64:26

>> Yeah. I mean the government still would

64:28

have access to things that we human

64:30

beings wouldn't have access to like like

64:32

like regular people um and um

64:36

particularly defense related weapons

64:39

related like for example u when they did

64:42

the uh ven venezuelan thing

64:45

>> um I don't think people in Venezuela

64:47

even understood like what even those

64:49

weapons were

64:51

>> I don't think we did they were described

64:53

as like yeah they were described as

64:54

something the the literal words used

64:57

were like alien like technology.

64:59

So we even we didn't know that um the

65:02

United States had access to uh that

65:05

quality of defense technology until that

65:07

incident happened. So there are

65:10

obviously going to be secrets right

65:13

especially the highest stakes things um

65:16

I would say like building frontier AI

65:18

models is similar to that. Um, of

65:20

course, as more and more models are

65:22

getting open source, I think the

65:24

knowledge is diffusing, but still, uh,

65:27

the the true amount of details you need

65:30

to actually train a really amazing

65:32

frontier reasoning capability model is

65:35

still not like widely diffused. So, I my

65:38

my things my my my hypothesis is that

65:42

um, whatever is extremely high stakes

65:45

will still not be widely diffused. It

65:48

it's it it'll at least there'll be

65:50

enough structures in place to keep it

65:52

secret.

65:53

>> Forever.

65:54

>> Not forever, but for a while.

65:56

>> For a while.

65:56

>> Yeah.

65:57

>> That's the thing.

65:58

>> Long term. Sure. Like things do get out

66:00

and people understand.

66:01

>> It feels like long term is what I'm

66:03

looking at. Like look, when we're

66:05

looking at history, we're talking in

66:06

these like when we're looking at all

66:08

these different temples and all these

66:10

different things, we're talking about

66:11

thousands and thousands of years

66:12

>> and thousands of year time span in

66:14

between each individual one.

66:17

>> With our world, we're talking about

66:20

massive change in 200 years. Like this

66:22

country is 250 years old. Think about

66:25

how kooky that is.

66:26

>> Yeah.

66:26

>> That is a blink of an eye in history.

66:28

>> But do we do we understand everything

66:29

that happened in the United States?

66:31

>> No.

66:31

>> Exactly. So there are still some details

66:33

that are

66:33

>> sure

66:34

>> hidden from us like we we don't fully

66:35

understand everything right

66:37

>> for now.

66:38

>> Yeah.

66:38

>> But my question is as time goes on 250

66:43

years from now is it even possible to

66:45

keep any secrets from anybody

66:49

>> and and is that a good thing? It might

66:51

be a good thing. It sounds horrible to

66:53

people because they're like, "Oh my god,

66:55

what about privacy?"

66:56

>> Right. But also what about lies?

66:58

>> Yeah.

66:58

>> No more lies. Like everyone's going to

67:00

know what you're thinking. Everyone's

67:02

going to know everything people do all

67:04

the time.

67:05

>> Yeah. I mean, if you're a true

67:07

surveillance state, obviously there are

67:09

no secrets,

67:10

>> right?

67:10

>> Um except about the government itself.

67:14

>> That's the problem.

67:15

>> Yeah.

67:15

>> Does it bottleneck with the government

67:17

or does it get to a point where there

67:20

you can't even have government secrets?

67:22

Because as technology evolves and as

67:25

human civilization evolves, secrets will

67:27

be less and less not just necessary but

67:29

secrets. Secrets will be problematic

67:31

because they'll be an impediment to

67:33

knowledge. There'll be impediment to

67:34

understanding the true

67:36

>> the true scope of what the world is like

67:38

the true nature of all of our various

67:40

moving parts.

67:41

>> Yeah. May as long as the human quality

67:44

the intrinsic human quality of curiosity

67:46

and truth seeekingness which is you know

67:47

universal. that's existed ever since we

67:50

known human beings. If that continues

67:53

and that continues to be the case, then

67:55

people will have enough incentives to

67:58

figure out the truth.

67:59

>> Yeah.

68:00

>> And and they if something is actually

68:02

hard to get to, it only motivates you

68:04

more to actually go and find it.

68:06

>> For sure. But so my question is where

68:08

does this all go? you know, and you

68:11

obviously work in AI and when you think

68:14

about AI and when you think about just

68:15

technology in general and you

68:17

extrapolate, you just take it from here

68:19

and you just plotted out like what is a

68:23

possible scenario of 250 years from now?

68:25

Like what does it even look like? What

68:27

does the United States look like at 500

68:29

years old?

68:30

>> It's very hard to know. I I I'll be very

68:32

honest. I I I think it's very hard to

68:34

know even 5 years from now how it's

68:36

going to look like.

68:37

>> That's crazy.

68:38

>> Yeah. Five years ago was like

68:40

>> five years ago whoever is at the top

68:42

most in AI I'm I don't even consider

68:45

myself like that but whoever is at the

68:46

most frontier level of decision-m in AI

68:49

5 years ago I don't think they predicted

68:51

the exact state we are in today nobody

68:55

did if they did they would have already

68:57

procured all the compute and like you

68:59

know manufactured all the chips bought

69:00

out all the fabs they would have done

69:02

all that right just this counterfactual

69:05

everyone's like bottleneck by not having

69:07

enough comput and like we have we don't

69:09

have enough chips, we don't have enough

69:11

power. These are all the problems that

69:13

if you invite anybody in AI and ask what

69:14

is the bottleneck in AI today and

69:16

everybody would say power. I think

69:18

Jensen was here and he said the same

69:19

thing, right?

69:20

>> Yeah.

69:20

>> But okay, like if you predicted this

69:23

exact state 5 years before,

69:26

wouldn't you have secured enough power

69:28

and started building more power plants

69:30

yourself and start getting permits and

69:31

like started like planning out capacity?

69:33

No. Nobody did that.

69:34

>> No. Everything is reactive to the demand

69:37

that we're having today. So,

69:38

>> and that's just 5 years.

69:39

>> Yeah, that's just 5 years. So, when you

69:41

ask me to predict 250 years, like I just

69:43

have to honestly say I don't know.

69:45

>> Do you ever sit back and think about it

69:47

though? What it could be?

69:48

>> I do think about it. So, there are like

69:50

lot of fun. I I I I use perplexity a lot

69:53

for these kind of things. Um especially

69:56

this new feature computer inside it. And

69:59

um one one one this is just for

70:01

hypothetical scenarios. Let's say there

70:03

is an AGI, right? And I I've seen you

70:06

ask a lot of people about this and um

70:08

and um a lot of conventional answers is

70:12

like, oh, like we'll just become

70:13

managers of the AIS, don't worry.

70:16

>> But um if if the price of cognition is

70:19

the price of compute, managing an AI is

70:21

also

70:22

pretty much doable by the AI itself

70:25

because it's the bottleneck is not like

70:28

unique cognition capability there. So

70:32

the value of the society will

70:34

automatically shift to what is scarce

70:36

and uh fundamentally what has been

70:38

scarce is like asking like highquality

70:41

questions about things. Okay like what

70:43

if like we just completely spend all our

70:46

time understanding the past like that's

70:48

an interesting endeavor. It was not cool

70:50

before but it'll it'll become cool

70:52

again. Um and like we usually used to

70:55

view like archaeology or history as not

70:58

something that's like worth having a

70:59

career in because it doesn't pay well.

71:01

But what if it actually starts paying

71:03

you a lot more now that like actual

71:05

knowledge works being done by AIS and

71:07

like it's all mundane and all the price

71:08

of that is basically at zero,

71:10

>> right? And archaeology would be one of

71:12

the few things that it wouldn't have

71:13

access to because it doesn't have the

71:16

actual ground. It can't get into the

71:18

ground and do the scans and

71:20

>> No, let's say we have like robots to go

71:22

do that.

71:22

>> Mhm.

71:23

>> But but you're still going to be the one

71:25

probing, right?

71:26

>> Because you have incomplete information

71:27

all the time. Even the idea of like okay

71:30

let's go explore this particular area

71:33

let's go understand better or let's

71:34

let's go try to reverse engineer that

71:36

let's go try to build this again oh how

71:38

would it be if we wanted to do the same

71:40

thing on the moon there are like so many

71:41

interesting projects to work on for us

71:44

as long as we are we stay curious and we

71:46

stay interested in like a lot of things

71:47

that we've done before and trying to

71:49

understand like civilization

71:52

that I'm not really concerned about like

71:54

what things we get to do we might be

71:56

doing a lot more cool things for what

71:57

it's worth like I I don't know if

71:59

anybody will be like coming and telling

72:00

you that, oh, it's so cool to like open

72:02

an Excel sheet every day and make

72:04

financial models, right? Compared to

72:06

like

72:07

>> there's got to be somebody out there

72:08

that likes that.

72:09

>> I mean, there's something about like the

72:11

task you do and and and what you get

72:13

paid for, like what is the job title,

72:15

blah blah blah. And some people

72:16

associate their personal worth with like

72:20

where they work at and how much they get

72:22

paid. And I think that that thing is

72:24

going to collapse in in a in a in a

72:26

world where like the price of all that

72:28

cognition is going to be the price of

72:30

compute.

72:31

>> What do you think happens to people if a

72:36

large percentage of jobs get replaced by

72:39

AI?

72:40

>> I think they'll find new things. We've

72:43

always gravitated towards things that

72:45

are scarce because that's where the

72:47

value lies. And so if if um you know

72:53

have you one one interesting analogy is

72:58

um have you do you the Gulf States where

73:01

there's an abundance of resources and

73:02

they export their resources to other

73:05

states and that pays for the whole

73:06

state. You know how like they they offer

73:09

everybody um free electricity,

73:12

subsidized health, subsidized education

73:14

and like no taxes. When I first went to

73:17

Dubai like in um almost like 20 years

73:19

ago, um

73:22

they told me like people don't pay taxes

73:24

here and nobody pays for electricity

73:26

here and uh education is like super

73:29

cheap. And I was like, wait, how is that

73:31

real? and and um and uh and and the way

73:36

that's real is that I mean of course

73:38

Texas also has no taxes and you know any

73:40

well-run state can do this but the way

73:42

it's happening is that because the

73:44

government provides you all these things

73:46

it becomes a rontier state like you

73:49

offer political acquisitions to the

73:51

state and u what ended up happening is

73:55

citizens there expect the state to find

73:57

them jobs expect the state to take care

73:59

of like job displacement for them so

74:01

they don't worry. So, it made them a

74:03

little more lazy. So, that's not a good

74:05

future to have where u some people talk

74:08

about AI subsidies and AI dividends that

74:10

that that get paid to everybody. I think

74:12

we need to do some form of that, but

74:14

that that in entirety won't solve the

74:16

problem,

74:17

>> right? Well, the thing about PE

74:21

human nature is sort of undeniable. And

74:24

if you give people the ability to be

74:26

lazy, a large percentage of people will

74:28

take that.

74:28

>> That's right.

74:29

>> A large percentage won't though.

74:30

>> Yeah. There's going to be enough people

74:32

that are inspired to do something and

74:34

they say, "Okay, well now my basic needs

74:35

are taken care of. Let me pursue my

74:37

actual interest and find purpose in

74:40

that." Because that's a lot of people

74:42

find purpose in whatever their

74:43

occupation is. Yeah.

74:44

>> And if we can shift that to finding

74:47

purpose in what your actual interests

74:48

are and then really pursuing something,

74:51

whatever it is in that, then you'll

74:52

still have meaning in your life.

74:54

>> And we've keep coming back to the cur it

74:56

keeps coming back to staying curious.

74:58

>> Yes. and and and finding value in your

75:01

relationships, your your the family, uh

75:04

caring for each other. Um if you ask a

75:07

lot of retired people, actually retired

75:08

people is a good demographic to

75:10

understand what would happen, what what

75:12

are things people find meaning in after

75:14

like work's taken off them. And all

75:17

majority of the answers are always like

75:18

family, caring, you know, personal like

75:22

like relationships and uh community like

75:25

these are the things retired people keep

75:27

doing to like you know keep themselves

75:29

active and wake up every day and have

75:31

something to look for. So all those

75:33

things will become even more important

75:35

at a time when like work itself doesn't

75:38

mean much.

75:39

>> Mhm.

75:40

>> Doesn't mean humans won't be status

75:42

seeking. I think we'll still be but

75:44

status is not going to come from whether

75:47

you're working at you know like a

75:49

particular famous bank or a tech company

75:51

or whatever. It'll be driven by like um

75:54

how interesting you are. Are you

75:56

interesting to talk to? When I can talk

75:58

to an AI like despite that are you still

76:01

interesting to talk to? Are are there

76:02

certain things I get out of talking to

76:04

you that completely change my

76:06

perspective about like bunch of things

76:08

or is it just fun to hang around you? um

76:12

can we have a compounding relationship

76:13

together? And and I think again it goes

76:16

goes back to like you know being curious

76:18

about things.

76:18

>> Well, this is best case scenario, right?

76:21

Worst case scenario is civilization

76:23

upheaval, chaos, civil war,

76:25

>> and it's possible. It's possible even

76:27

without an AI,

76:28

>> right?

76:29

>> Exactly.

76:30

>> Look, we've gotten real close to it a

76:31

couple of times.

76:32

>> Exactly.

76:32

>> Yeah. So and and and and and we did not

76:34

need an AGI like scenario for a

76:38

civilizational collapse in the past as

76:40

you clearly seen,

76:41

>> right?

76:41

>> A calamity can just take out all of us,

76:44

wipe out everything.

76:45

>> Sure. Especially natural ones.

76:46

>> Yeah. That's why I'm not a big fan of

76:48

like everybody claiming that um the AI

76:50

is going to, you know, kill us or like a

76:52

AGI is going to destroy humanity and

76:55

like it's too dangerous and we all need

76:57

to stop doing these things, but at the

76:58

same time continuing to build data

77:00

centers and continuing to make money.

77:01

you you you have to have one consistent

77:03

position. My position is that um whether

77:08

AI or not, I think being curious is

77:10

going to serve you really well. Um I

77:13

think it's going to help you have a

77:14

better life. And um there are two paths

77:16

to curiosity. One that can kill it and

77:18

one that can supercharge it. In my

77:21

opinion, the one that kills curiosity is

77:23

algorithmic feeds. like

77:25

>> the the brain rot that you're fed every

77:28

day with just, you know, just continuous

77:30

doom scrolling.

77:31

>> That's bad.

77:33

>> Um, and the one that can supercharge it

77:34

is AI.

77:36

Okay. Like now that you could just ask

77:39

whatever you want if everybody has like

77:41

a pull it up Jamie for them, you know,

77:44

>> right?

77:44

>> And and that's amazing. So, okay. So,

77:46

all you have to do is

77:48

be curious about a lot of different

77:50

things and and of course talk to

77:51

interesting people. um engage in

77:53

interesting activities together. If

77:55

money is no longer an issue, you can

77:57

fund passion projects yourself. You

77:59

don't have to like require government

78:01

funding or right

78:02

>> venture funding.

78:03

>> Like what if you just wanted to build a

78:05

mini cave yourself, okay? Like you find

78:08

a piece of land somewhere. There's a lot

78:09

of land in America.

78:11

>> Uh way more land than we know what to do

78:13

with it. And um and and and surely we

78:16

can build a lot of interesting things

78:17

there.

78:18

Well, that's a good glass half full

78:22

scenario. And one of the things that I

78:24

keep coming to is this whole idea of

78:27

people working and making money and

78:30

having careers and having portfolios and

78:33

bank accounts and all. This is all very

78:36

recent in human history. Yeah. Very very

78:38

recent. Very recent. It's very recent.

78:40

But we've become accustomed to this as a

78:42

way of life. And we

78:43

>> and Microsoft Microsoft built this

78:45

concept of a knowledge worker because

78:46

they wanted to sell more office

78:48

software.

78:49

>> Really?

78:50

>> Yeah. Like like this whole idea of

78:52

putting a PC on every desk and and

78:55

making you like glue to the PC was their

78:57

that was Bill Gates vision. Put a PC on

78:59

every desk.

78:59

>> That wizard. What a what a

79:02

incredible accomplishment because boy

79:04

did they nail it.

79:05

>> Yeah. So it was not about making

79:07

computing like beautiful or anything in

79:09

the way like Steve Jobs envisioned it,

79:11

>> right? It was just about comput sell

79:13

more software, sell more computers

79:15

because that way you can sell more

79:16

software

79:18

>> and and if you sell more software, you

79:19

become rich and and and and the company

79:22

just was a machine that was just, you

79:25

know, built it's essentially a large

79:26

sales machine that's built to sell

79:28

software

79:30

and and and uh and uh now they sell

79:33

cloud, but whatever like that that

79:34

that's essentially the uh the reason

79:36

that like you know we all got trained to

79:39

use software. ware people went and did

79:42

tutorials on how to use Excel, how to

79:45

use Word, how to use all these email

79:47

tools and then now that became the

79:49

upskilling you needed to go work at a

79:51

different companies and then write code

79:53

and like whatever, right? So that if

79:55

that part is going to be done by an AI,

79:56

it's not necessarily a bad thing

79:59

because this is not actually the way you

80:02

feel like real purpose and fulfillment

80:03

in your own life. If if you were never

80:06

exposed to that, whatever you had as the

80:09

intrinsic curiosity in you,

80:12

that that's probably what you should be

80:13

doing.

80:14

>> Yeah. There could be a completely new

80:15

way to live life

80:16

>> where we're not

80:18

>> dependent upon labor for basic needs and

80:22

but then it's going to be incumbent upon

80:24

people. They're going to have to figure

80:25

out a way to be either self-starting or

80:28

we're going to have to expose people to

80:31

things that going to excite their

80:32

curiosity and make that a mandate.

80:34

>> Yeah. It it has to start from schools.

80:37

>> Yeah.

80:37

>> And um as long as we keep rewarding

80:40

people for having answers

80:42

instead of asking interesting questions,

80:45

it's it's going to be a difficult

80:47

change. Like in schools, you're always

80:49

rewarded for being smart based on

80:51

whether you have answers to like 20

80:53

different questions. Like who cares?

80:55

Like all those 20 questions can be

80:57

answered by AIS. Um, have you ever like

81:00

flipped the script where you say, "Okay,

81:01

like I'm going to the smartest person in

81:03

the room is the one who asks the most

81:04

interesting questions."

81:06

>> Okay. Like what what kind of students

81:08

can you cultivate based on that?

81:11

>> Like imagine if the room had no pressure

81:13

to always know the answer,

81:15

>> but the freedom to ask a a lot of

81:18

questions,

81:18

>> right? Because sometimes when someone

81:19

asks a question, it'll it'll

81:23

make you pause and go, I never even

81:24

thought of that, but that's it. Like

81:27

that's the question. Yeah.

81:28

>> And it takes a com I mean so many people

81:31

have so many different perspectives

81:32

which is one of the more interesting

81:34

things that I've experienced doing this

81:37

podcast is I get to talk to so many

81:39

different people and

81:40

>> they vary so widely. There's so many

81:44

different ways of looking at the world

81:45

and so many different ways of engaging

81:47

with the world and so many different

81:49

things that people are fascinated with

81:50

that they spent their entire life

81:52

studying and and pursuing. It's like you

81:55

get this rich tapestry of the human

81:57

experience that's just I would have

81:59

never been exposed to this many people.

82:02

Yeah.

82:02

>> And in turn I've been able to expose

82:04

these people to all these other folks

82:06

that are just listening and watching

82:07

right now. And it's incredible.

82:10

And it's such a for me it's like the

82:13

perfect job. I've never had a job that

82:15

more aligns with my own personality as

82:17

much as this because I've always been

82:20

that kid like shut the up with all

82:21

the questions. I've always been that

82:23

kid. That that's the system, right? It's

82:24

not it's not your fault,

82:26

>> right?

82:26

>> Like it's actually the reason you're

82:28

successful now is the exact thing that

82:30

people told you to shut up about in the

82:32

past,

82:33

>> right?

82:33

>> Yeah.

82:34

>> Don't you know, hey, you you you know,

82:36

stop bothering my lecture,

82:39

you know, asking all these unrelated

82:41

questions. It's it's mainly a

82:42

frustration of the teacher that they

82:44

don't have the answers to you,

82:46

>> right? Or

82:46

>> Sure.

82:47

>> and and and um and now that that

82:49

bottleneck is gone. We did this

82:51

experiment with with one one instructor

82:53

at MIT who taught the introduction to

82:55

biology class where uh he came and told

82:58

us that he's going to give perplexity to

83:00

all the kids all the students and um

83:02

they would use it as part of the

83:04

lectures. So so instead of fighting AI,

83:08

you just give AI to everybody and let

83:10

them ask whatever questions they want

83:12

and they can actually use it in the

83:13

exams too.

83:14

>> So wow. So how do you even design

83:17

questions for an exam

83:20

u in in such a world is maybe you just

83:22

encourage people to pose a question that

83:25

AI can't answer right now and that

83:28

becomes your research project and you

83:31

turn everybody into a scientist

83:33

fundamentally like there's this belief

83:34

that scientists have to go through a

83:36

rigorous PhD and like you have to get

83:38

you know accredited by like an amazing

83:40

university to be that sure but uh anyone

83:44

who's curious can be a scientist. The

83:46

only thing that's required to be a good

83:48

scientist is intellectual humility to

83:51

understand that you could be wrong about

83:52

things. Things that everyone takes for

83:55

granted. You could still question them.

83:57

And when you when you're presented with

83:59

new evidence and new data, you're

84:00

willing to change your mind and you're

84:02

willing to operate with ambiguity and

84:04

uncertainty about the world. That's

84:07

that's basically all the qualities you

84:08

need to be a scientist. And you can run

84:11

your experiments, you can gather data,

84:12

you can gather evidence, and you can

84:14

consult people, you can bring in experts

84:16

and talk to them. And and as long as

84:18

you're uncovering more and more about

84:20

the world, you are a scientist. You

84:22

don't need a PhD to feel that you're,

84:25

you know, allowed to be a scientist or

84:26

not. And I think that's the most

84:28

important um quality we need uh to

84:32

inculcate in our kids, the upcoming

84:35

generation, so that they all feel more

84:37

liberated. Okay. Like finally I don't

84:39

have to memorize this textbook or these

84:41

lecture materials and like I don't have

84:43

to feel bad if I get like 12 out of 20.

84:46

Okay, who cares? Like AI is always going

84:48

to get 20 out of 20. That's not what

84:50

you're meant to be like good at. Of

84:52

course, master the foundations, the

84:53

basics. Great. But your job is to

84:56

actually pose interesting questions.

84:59

>> Yeah. And the intellectual, excuse me,

85:01

intellectual humility is so important

85:03

because one of the things that was

85:05

really weird about the whole COVID

85:07

pandemic was that we weren't supposed to

85:09

question science.

85:10

>> Yeah.

85:10

>> It was like that or when Fouchy said if

85:13

you question Anthony Fouchy, you are

85:16

questioning science.

85:17

>> That's because they try to assign

85:19

credibility through their degrees.

85:21

>> Yes.

85:21

>> Through their affiliations,

85:23

>> appeal to

85:24

>> but not through the scientific method.

85:25

>> Right. Anybody should be allowed to ask

85:27

questions as long as they are open to

85:30

new evidence.

85:31

>> Yeah.

85:32

>> And that's the most important quality of

85:33

a scientist.

85:34

>> Well, the scientific method alone, I

85:36

mean, it's one of the most important

85:38

things that we can use to try to figure

85:40

out what's real and what's not real. And

85:42

as soon as someone says don't use it.

85:44

>> Yeah.

85:45

>> So, don't question. Well, wait a minute.

85:47

And then there was this an actual

85:50

government push to silence questioning

85:53

and legitimate researchers were kicked

85:55

off of Twitter because they didn't back

85:57

the narrative.

85:58

>> Yeah.

85:58

>> Like this is all anti-science. This is

86:01

not this is not you're questioning

86:03

science. Well, science demands

86:05

questioning.

86:06

>> Yeah.

86:06

>> It's what it is.

86:07

>> Yeah. When you don't understand

86:09

something, the the best thing you can do

86:10

is ask all possible questions,

86:12

>> right? Right? And so curbing that is

86:15

almost like a way of saying, "Look, I'm

86:17

going to tell you what happened. You

86:19

need to believe in my worldview and I'm

86:21

not open to new perspectives."

86:24

>> I wonder if anybody has used AI to try

86:28

to map out possible scenarios for where

86:32

technology leads human civilization and

86:35

what could be done to mitigate the

86:36

problems and push it in the proper

86:38

direction. like have a bunch of

86:40

different models of how this could play

86:42

out.

86:43

>> Yeah.

86:45

I mean, uh I I try to do that for fun,

86:48

but I haven't done it in a serious

86:49

enough way to have like a proper answer

86:51

to that,

86:51

>> right?

86:52

>> But, uh I think like, you know, um a lot

86:56

of things that we are doing today will

86:58

not be considered needed or valuable.

87:02

I and and and maybe a little bit of

87:04

taking our own lessons from the past. I

87:06

don't know if you when you grew up as a

87:08

student, did you have to like be good at

87:10

mental math like multiplying arbitrary

87:12

numbers? Was that considered a sign of

87:14

smartness or remembering people's phone

87:16

numbers or something?

87:17

>> Well, you had to because there was I

87:18

mean you had little address books.

87:20

That's what we used to carry around like

87:21

a little I had a little address book

87:23

that I keep on my desk. Yeah,

87:24

>> it's a little tiny thing with

87:25

everybody's number and name. That's the

87:27

only way I knew people's numbers.

87:29

>> And I remembered a bunch of them like

87:31

all my friends. I had all my friends. I

87:33

don't have any of my friends numbers

87:34

remembered. Yeah. Yeah, maybe my wife

87:35

and my friend Eddie. I have two numbers

87:38

in my head.

87:39

>> But But was there a time when people

87:41

thought somebody was smart based on how

87:43

good their memory power was?

87:45

>> Oh yeah, definitely.

87:46

>> But would you would you say that now?

87:49

>> Well, people are impressed if you know

87:51

things now. You know, I have a bunch of

87:54

like weird information obviously that

87:56

I've gathered through so many years of

87:58

doing this podcast and just so many

87:59

years of being curious. You know, like

88:02

sometimes even my own daughter is like,

88:03

"How the do you know that?" I'm

88:04

like, "This is what I do." Like that's

88:06

my thing. Yeah. You know, I pay

88:08

attention to stuff. Yeah.

88:09

>> But yeah, I mean, memory itself is

88:12

always very impressive. And someone has

88:14

an excellent memory. Yeah. And can pull

88:16

up facts of the past. We automatically

88:18

equate that to intelligence.

88:20

>> Yeah. I I I think it's impressive, but

88:22

it's not necessarily a sign of being

88:24

intelligent, right? Like I think it's

88:27

just a look You have a very fast lookup

88:29

table in your head. That's great. It's

88:31

very valuable. Um, but I still think

88:34

like being smart is all about posing the

88:36

most interesting questions.

88:38

>> Also, the decisions that you make and

88:40

whether or not you self-correct when you

88:43

make mistakes.

88:43

>> Yeah.

88:44

>> Yeah. All those things.

88:45

>> Exactly. So, when you when you have an

88:47

amplifier to your intelligence like an

88:49

AI all the time where lookups is

88:51

essentially something you can delegate,

88:54

um, reasoning for decision-m is

88:56

something you can delegate. But posing

88:58

the right questions to gather the right

89:00

data and then forming your own judgment

89:02

based on what it reasons and comes up

89:04

with and finally having the courage to

89:06

make the decision. That's still you.

89:08

That agency, that intrinsic curiosity to

89:11

ask the right question, the scientific

89:13

intellectual humility to like, you know,

89:15

gather new evidence, always questioning

89:18

your beliefs, that that is still you.

89:20

And so um I feel like that is

89:22

essentially what would be considered

89:24

smart in the ages to come if somebody's

89:27

like a you know like a proxy scientist

89:29

or whatever like no more uh doesn't have

89:32

to go to like MIT or Harvard and get a

89:34

PhD to be a scientist or to be

89:36

considered a scientist because all

89:38

scientific literature is open and like

89:39

it's accessible to everybody and you you

89:41

can cons you can even take a paper

89:43

written by an expert and and use an AI

89:46

understand it deeply ask a lot of

89:48

questions and maybe even disprove what

89:49

they claim to be true. That's the whole

89:53

peer review process, right? The

89:55

peerreview process is all about

89:57

questioning somebody's paper. And um

90:01

that's why like you know what whatever

90:03

you said happened in the co days is is

90:05

wrong. Like you should be allowed to ask

90:08

questions about even eminent scientists

90:11

work. It's okay. Like if you're dumb and

90:13

you had had the wrong questions, sure,

90:15

you're going to learn from that. the

90:17

it's worse than not being allowed to ask

90:19

the question.

90:19

>> Yeah, agreed. It's going to be

90:21

interesting to see what the future of

90:23

education looks like. Like how valuable

90:25

are degrees when essentially AI is going

90:28

to be able to do the majority of

90:30

whatever work you need done on variety

90:33

like

90:34

>> how how good are they right now at uh

90:38

just law like you could ask questions

90:42

pretty pretty amazing right?

90:44

>> Yeah.

90:44

>> How good are they at mathematics?

90:46

Perfect. Like how good are they at

90:47

coding? Way better than people.

90:49

>> Yeah. And at a certain point in time,

90:51

it's going to be interesting that like

90:52

what is education now? Is education just

90:55

providing you with information because

90:56

that information is readily available.

90:58

Or is education teaching you how to

91:01

think?

91:01

>> Yeah.

91:01

>> Teaching you how to pursue your

91:03

interests and be curious and have

91:05

intellectual humility and understand

91:06

what you know, what you don't know.

91:08

>> I think that that's what it should be. I

91:11

still think institutions will preserve

91:13

their brand value because there is a

91:16

certain aspect of education that's

91:18

outside of learning which is just having

91:20

access to other curious and intelligent

91:23

people.

91:23

>> Sure. Community.

91:24

>> Yeah. And and brands attract good

91:26

communities, peer groups, blah blah

91:27

blah.

91:28

>> Mhm.

91:28

>> But the actual process of learning

91:30

itself has to change and and and what

91:32

you're rewarded for has to change. So

91:34

fundamentally everything you know flows

91:36

down is downstream of the incentive,

91:39

right? So if the incentive is to score

91:41

the highest on the exam based on

91:42

answers, you're not really changing

91:44

much. If you need to change that

91:47

process, you need to change the process

91:49

of what do you reward a student? Like

91:50

what is A+ or A,

91:52

>> right?

91:53

>> That that that's where we need to start

91:54

at.

91:55

>> Well, it's also the we you know, we

91:56

talked about this the other day that the

91:58

education system in this country was

92:00

designed to make workers and that's what

92:02

they did when they first started doing

92:04

it and the turn of the

92:05

>> curriculum was designed around that.

92:07

Yeah. Well,

92:08

>> in India, it's still the case, by the

92:10

way.

92:10

>> Really,

92:10

>> even if you're a computer, even if you

92:12

go into a computer science degree,

92:14

>> I don't know if it's still the case. I

92:15

shouldn't misspeak, but at least when I

92:17

was there and for many years after the

92:19

first two years, you just spend learning

92:20

hardcore electrical and mechanical

92:22

engineering. You would learn like

92:24

welding, using lathe machines. You would

92:26

you you would um have to like go and

92:28

like do workshops, carpentry,

92:31

uh a lot of these things. It was fun.

92:33

>> I would think there's be a lot of value

92:34

in that. So, so in hindsight, I actually

92:36

think it was fun to learn soldering and

92:38

like how to like make circuits on red

92:41

boards and learn to circuit boards.

92:43

>> But, um, if somebody was just interested

92:46

in some, you know, just writing code,

92:48

let's say, back then, all this is kind

92:51

of like pointless to learn, but you had

92:53

to go through it to be qualified as an

92:56

engineer. M

92:57

>> so um and and and the reason the

93:00

curriculum was designed that way is

93:01

because that's what the labor force was

93:03

required back then to build like oil

93:06

factories and like all these things. So

93:07

you had to learn mechanical engineering,

93:09

you had to learn fluid mechanics,

93:10

whatever. But um I think that that that

93:13

should also change because if if if the

93:15

way like you do work changes then what

93:17

you're trained for in college should

93:19

also change. And u it's much harder to

93:22

change these things. You know pe people

93:24

are much slower. they're scared to do

93:26

changes. Disruption is always like

93:27

looked down upon and um so I think we

93:31

let's at least start at the incentive

93:32

structure uh right from the schools,

93:35

right from the colleges like let's not

93:36

like reward people based on like how

93:38

much they know.

93:39

>> Well, if it seems like in the future

93:41

when things do radically change and they

93:44

seems like they're inevitable, they're

93:45

going to radically change.

93:48

Universities and schools are going to be

93:50

rewarded for having developed thinkers

93:53

that are able to adapt to this new

93:55

world.

93:56

>> That's right.

93:56

>> Yeah. So, they're going to have to

93:58

figure out how to adjust their

93:59

curriculum.

94:00

>> Yeah.

94:01

>> Because the the tools are so spectacular

94:04

now that just this idea of just

94:06

memorizing information is it's not

94:09

that's not what you're going to need to

94:11

get by in the future.

94:12

>> It's not. And and I I guess like one

94:14

proxy different schools use is like

94:16

maybe if more entrepreneurs arise out of

94:18

your school, you probably u created a

94:22

lot of independent thinkers.

94:24

>> Mhm.

94:24

>> Um because they are like willing to take

94:26

a fresh perspective towards a problem,

94:28

>> right? and and build their own thing

94:29

from scratch. And and fundamentally

94:32

that's what America America's always

94:33

been about is you know some the American

94:36

dream of coming here and like having

94:38

your own idea and still be taken

94:41

seriously by a bunch of people. The

94:43

whole idea of venture capital Olympics

94:44

this year or like family and friends

94:47

around this whole idea of just having

94:49

your friends help you to bootstrap a

94:50

business and then turning it into a

94:52

success and success doesn't mean like

94:54

multi-billion or 10 billion or whatever,

94:56

right?

94:56

As long as it pays you enough that you

94:58

don't have to work for somebody else and

95:00

you can live a fulfilling life and you

95:02

can just go explore your passions,

95:04

that's success. That's actually a better

95:06

success than

95:08

>> creating a company based on what other

95:10

people want you to do and then hating

95:12

your job for it.

95:13

>> Yeah. And having a yacht and being

95:15

miserable and working every day.

95:17

>> And that's why I said like not the the

95:18

the smartest or the richest people are

95:20

not always the ones who have the most

95:22

fulfilling lives. The most curious

95:23

people have the most fulfilling lives

95:25

because they have better relationships.

95:27

They're actually able to sit and look at

95:29

something and, you know, be curious

95:30

about it instead of like being worried

95:32

about what's going on.

95:34

>> What What did the American dream What

95:36

was it to you when you weren't in

95:38

America? Like what what is it like over

95:40

like what is how is it discussed?

95:43

Well, um to me like I always thought

95:47

America is the only country where you

95:48

can come here and um have an idea and

95:51

people listen to you and uh and and and

95:54

encourage you to go pursue it. The

95:56

risk-seeking culture is just incredible

95:59

here. Everybody everywhere else you kind

96:01

of are like either explicitly or

96:03

implicitly are forced to defer to

96:05

authority. Okay, like go and ask the

96:08

permission of this person, go and ask

96:09

the permission of that person or get

96:11

their approval or get their insight or

96:13

sure you can get their cons you can

96:14

consult everybody out there but if you

96:17

have a thought that challenges what they

96:19

believe in this country still encourages

96:21

you to like go pursue it

96:24

>> and um so yes like when I came here

96:27

obviously you know Google was the number

96:29

one company that everybody wanted to

96:32

work in but it's also the same country

96:34

where it allows you as a new person to

96:38

start a new idea that challenges one of

96:41

the biggest companies in in in in this

96:42

own country and actually wants it.

96:45

People actually want new ideas and um

96:49

and then you can consistently see that

96:51

there are like always going to be more

96:53

and more new ideas and new companies to

96:55

be created here. And so that spirit of

96:58

like questioning

97:00

is is encouraged a lot here. And and it

97:03

it happens in academic research. I

97:05

started off as an academic even there um

97:09

a lot of ideas when I had it um and I

97:12

would share it with people um you know

97:15

people actually give you very honest

97:17

feedback about things but they don't

97:19

stop you from working on anything

97:22

and and that's fantastic because that's

97:24

that's very fresh it's very liberating

97:26

>> and that's not anywhere else

97:30

>> I would say it's not

97:31

>> it's not in India

97:32

>> it's a simplification to say it's not

97:34

anywhere else But um

97:36

>> it's not as encouraged.

97:37

>> It's not as encouraged. The incentive

97:39

structures are not quite there and uh

97:42

ability to like be taken seriously for

97:45

some crazy ideas is is is why America is

97:48

still at the top.

97:50

>> But it's crazy to me that if the

97:52

American dream is so compelling and so

97:54

many people come here for it, why

97:55

doesn't the rest of the world sort of

97:57

adopt those values?

97:59

>> It's hard, you know, like

98:02

a lot of it is cultural. like America

98:05

was was was born was made from from like

98:10

you know a piece of land essentially

98:12

right um and u a lot of ideas that we

98:16

built here a lot of industries that we

98:18

built here were were all like created

98:21

here from nothing and that required you

98:23

to like go take bold risks I think Jeff

98:27

Bezos said this in some um podcast that

98:31

where else would you like be able to go

98:33

raise like a few million dollars for an

98:35

idea that has like 5 to 10% chance of

98:37

working

98:39

and then fail at it and still go and

98:41

raise another few million for your next

98:42

idea.

98:46

No, nowhere else. People are willing to

98:47

like people who get rich here actually

98:50

want to encourage and be part of

98:52

somebody else's crazy journey because

98:54

it's hard to pursue all crazy bets

98:57

yourself.

98:58

>> Mhm. So it's an ecosystem

99:01

and once something becomes an ecosystem

99:03

there's network effects. So it's very

99:05

hard to copy that elsewhere.

99:07

>> And so your value is measured in your

99:10

curiosity and your willing to work your

99:13

willingness to work on whatever it is.

99:15

Yes. That is your pursuit. Yes. And then

99:17

eventually adjusting and learning and

99:19

>> catching fire with one of them.

99:21

>> Correct. And and and you have to work

99:22

hard like I I you know like I I I I'm a

99:25

big believer in intense hard work. I

99:27

think uh not nothing great can be

99:29

accomplished by being soft and so all

99:33

this like recent push for you know

99:35

having a lot of work life balance this

99:37

and that sure if you have work life bal

99:38

if you if that's what you want and I

99:40

think there are certain jobs that would

99:42

give you that but when you're trying to

99:43

do something from scratch when you're

99:45

trying to create something from nothing

99:48

it's not meant to be easy

99:49

>> right

99:49

>> there are some sacrifices that have to

99:51

be made and you're signing up to be part

99:53

of that experience that that that

99:56

surreal joy you from doing something

99:58

that's felt almost impossible to achieve

100:01

and and uh and you're not doing you're

100:04

not like staying up late or waking up

100:05

early because you're getting paid more.

100:08

Maybe you might not get paid anything.

100:10

Maybe this whole thing goes to nothing,

100:11

but that that experience you're getting

100:14

of being part of something that feels

100:16

very hard to achieve is what you're

100:18

signing up for to be part of.

100:20

>> Yeah. And if you're not, find something

100:23

else.

100:23

>> It's fine. Respect that. Nothing wrong

100:25

with that.

100:25

>> Exactly. and and and and the country has

100:27

enough jobs to provide for all kinds of

100:29

like needs, right? And and everybody

100:31

goes through different phases in their

100:32

life. Sometimes they feel a little lazy

100:34

or like disillusioned. Okay. And and so

100:37

um what I like about this country is

100:39

that there's lot of curious people here.

100:41

There's a lot of like so many different

100:43

people, you know, like whether they use

100:45

AIS or not AIS, they're all like finding

100:48

meaning in like so many interesting

100:49

projects. Well, obviously I don't know

100:52

any other country really because I was

100:53

born here, but the people that do talk

100:57

to me about what the American dream is

101:00

like from another country, they're the

101:02

most passionate and the most supportive

101:04

of this this idea, this experiment in

101:07

self-government and this this the

101:10

>> just the whole idea that the country

101:13

operates on that anybody can chase their

101:15

dream that you can if you have a dream

101:18

and you're willing to work hard, you

101:19

could actually do it in this country.

101:20

>> That's right.

101:21

>> Yeah. That's, you know, it's most the

101:25

people that are most passionate about

101:26

that idea often times are people that

101:28

come from somewhere else where that

101:29

wasn't available

101:30

>> and and it's not just like, you know,

101:33

people coming from one particular

101:34

country or another. It's it's it's the

101:36

attitude. It's the the way the system

101:39

works and rewards you to like be bold

101:41

and take bets against established

101:43

players. It's okay, right? It's okay to

101:45

like be an upstart, a challenger. And

101:47

people love that like underdog and I and

101:50

I think you know that's fantastic like

101:51

and and that culture is continuing. Yes,

101:54

there are like multi-trillion dollar

101:55

companies here and they're all going to

101:56

become even bigger but people still want

102:00

the young hungry person to also be

102:04

successful.

102:05

>> Yeah. Well, they they love disruptors.

102:07

>> Yeah.

102:07

>> And people love underdogs in this

102:10

country.

102:10

>> Yeah. It's it's it's it's universal.

102:13

It's not specific to technology,

102:15

>> right? Like I'm sure everybody would

102:17

love underdog story that wants to go

102:18

against like Coca-Cola or Pepsi or

102:20

something too.

102:21

>> Sure. Yeah.

102:21

>> Oh, in sports it's our favorite thing.

102:23

>> In sports. Yeah.

102:24

>> We don't like when the guy who's

102:25

supposed to win wins. We love when the

102:27

guy who's not supposed to win triumphs.

102:29

>> Yeah.

102:29

>> Yeah.

102:29

>> The underdog story.

102:31

>> Yeah. That's a very uniquely American

102:34

story

102:35

>> to me. That's what this this this

102:37

country is. I mean, sure, there's a lot

102:40

of obstacles and challenges just like

102:42

every other country. There are things

102:43

here that are challenging, but it's one

102:46

thing that has consistently stayed true.

102:50

>> One of the big fears that people in

102:51

America have uh about technology in

102:54

particular is that without

102:57

being aware that this was going to take

102:59

place. Everybody gave up their data.

103:02

Everybody gave up their data and didn't

103:04

recognize it was a commodity. That in

103:06

turn made these corporations immensely

103:09

wealthy and powerful. And then

103:11

>> they have the ability to shape

103:13

narratives

103:14

>> and that that concerns people because

103:17

using their ideological position as

103:22

leverage to try to push that through

103:26

technology that has immense control and

103:28

influence over people. and that we

103:31

didn't see technology and corporations

103:33

as having that much control over how

103:36

society views itself and how we interact

103:39

with each other.

103:40

>> And there's a real real concern that

103:43

these companies got so big and have so

103:46

like there's a guy named Robert Epstein

103:48

who's done a lot of work on um narrate

103:52

or curated search engine results and how

103:55

much that can have you read seen any of

103:56

his stuff?

103:57

>> I think I've seen this. Yeah. how much

103:58

that can affect elections, how much that

104:01

can affect people's perceptions on any

104:04

societal issue that's coming up.

104:06

>> Yeah.

104:06

>> And it's concerning. It really is

104:08

because they do curate search results.

104:11

It's not simply, you know, you just run

104:13

it out there and you get this is the

104:15

data. No, you get, you know, if you look

104:17

for specific political figures,

104:19

depending upon where they fall in the

104:21

right or left spectrum and depending

104:22

upon which way the company forms the the

104:25

the corporation forms falls rather,

104:29

you'll get different results and that

104:30

sucks. You know, that's

104:32

>> it's very concerning that people don't

104:35

recognize they don't they don't have the

104:37

ability to see how that is dangerous for

104:41

all of society.

104:42

>> Yeah. to have that kind of power and

104:44

wield it in that way where you're not

104:46

being honest about accurate objective

104:48

information. You're pushing particular

104:50

ideologies.

104:51

>> Yeah. So I think it's kind of like u

104:57

this is almost an effect of the

104:59

asymmetry that exists between the amount

105:01

of AI power that centralized systems and

105:04

centralized companies have and the

105:05

amount of AI power as you as a sovereign

105:08

individual has.

105:10

So when you don't have the AIS to just

105:13

go judge for yourself like what you

105:15

should be reading and fed,

105:17

you're obviously like under the

105:18

influence of what

105:21

you know whatever big tech company's

105:22

controlling the information for. But

105:24

when you have access to all those AIs,

105:26

you can actually just customize what you

105:28

want to see by telling the AI like,

105:31

"Hey, this is what I think you should

105:33

actually question and tell me." Until

105:36

now, you never had that power for

105:38

yourself. you're finally getting it,

105:39

>> right?

105:40

>> And eventually we'll we'll be able to

105:42

have our own LLMs, like our own models

105:44

that we would be able to host in our own

105:47

hardware. We don't have to rely on like

105:50

one centralized model given to us by

105:52

like any specific um model company and u

105:57

using that you can shape it to your your

105:59

beliefs your custom you know your your

106:01

your custom data and and um so when

106:04

you're consuming a search result you can

106:06

actually ask that AI that you control

106:09

and you run so nobody can shut off

106:11

access to it to tell you like hey like

106:13

can you actually like give me a

106:15

contrarian perspective on this or like

106:18

Can you tell me if these search results

106:19

are actually biased? So, I think we need

106:22

to give individuals more sovereignty

106:25

with more access to their own AIS that

106:28

they own and run on a piece of hardware

106:29

they own themselves. And this is the

106:32

whole like this is going to be leading

106:33

to the whole rise of local AIS. So, as

106:36

AI models like today, they're very power

106:38

and efficient. They're running on large

106:39

data centers. that in in a year or two

106:41

from now whatever capability that exists

106:44

in the most power hungry data centers

106:46

will be you it'll be possible to run it

106:48

in some box that you own may not really

106:50

yeah

106:51

>> it's already happening

106:52

>> it's already happening that like there

106:54

are like interesting hardware projects

106:56

like the Apple Mac Mini Nvidia DGX

107:00

where you can actually host a reasonable

107:04

size model and and put it in a box and

107:08

have it run and you don't have to pay

107:09

for all the tokens it it it produces

107:11

you. You just have to plug it into your

107:15

power core and it works.

107:17

>> I know Duncan, my friend Duncan

107:18

Trussell, he does that.

107:19

>> Yeah. And and and today the capability

107:22

of that model that can run locally is

107:24

not quite there. So you would still

107:26

prefer to use something that runs from

107:27

the data center. But eventually this is

107:30

going to be a spectrum. There's going to

107:31

be some percentage of tasks that you you

107:33

would start delegating to this local

107:35

system. It'll be a hybrid model. And

107:37

over time, it could end up being the

107:39

case that you could buy something that

107:40

feels like a refrigerator for your home,

107:43

which is your own AI box,

107:45

and host a model that you control. So

107:48

nobody can arbitrarily shut off access

107:50

to it one day. And then you can you can

107:54

have that be your weapon against what

107:56

the big tech wants you to be fed or

107:57

believe in. M so

107:59

>> this is the only way we can fight this

108:01

because they have far more computing

108:02

power far more data far more algorithms

108:06

than you so the only way you can fight

108:08

that is you have something you own

108:10

yourself and with the rise of

108:12

open-source models open source LLM you

108:16

can just and and and and progress in

108:18

local hardware and and both Apple Nvidia

108:21

Intel they're all doing amazing work

108:22

here you could potentially change the

108:25

future and give people more power and

108:26

this may not be as expensive those

108:28

people think

108:29

>> well that's a good solution because I

108:32

I've always wondered like is are these

108:34

searches like using Google is that going

108:37

to be irrelevant one day because you

108:40

already can just ask your phone like I

108:42

most of the time if I want to have an

108:44

answer for something I just ask

108:46

perplexity it's like what is it and

108:47

instead of like having to sift through

108:49

all these Google searches yeah

108:51

>> and try to figure out what it's showing

108:53

me first and get to page three where

108:55

it's what I really want to know I can

108:57

get the accurate information, then

108:58

follow-up questions are instantaneous.

109:00

>> Yeah. And and and and even the models

109:02

that are running the Plexity app today,

109:04

they're all in the cloud. Eventually,

109:06

you'll be able to do that on on a box

109:09

that you own. You can still you can

109:11

still use the front end the UI of the

109:14

app, but you can control the compute

109:16

that runs on on on piece of hardware.

109:19

You you may ask why why do I care? Okay.

109:22

Like what if some someday like the data

109:24

center gets taken off like Iran was

109:27

bombing data centers,

109:28

>> right?

109:29

>> Or like what if someday like the

109:31

government decides that model is no

109:32

longer available.

109:34

>> You you want some control over like like

109:36

what models you can run and like you can

109:39

you may even want to shape it to like

109:40

your context that you never want to be

109:42

living on any data center

109:45

>> and and and and uh I think that's where

109:47

I believe the individual gets more

109:50

sovereignty against big tech.

109:52

And um that's how like we fight the

109:55

surveillance or like centralization of

109:57

power.

109:58

>> Yeah. And c certainly pushing

110:00

narratives. Um what do you think happens

110:03

with social media because social media

110:06

and as you were talking about before

110:07

like algorithms like it's one of the

110:09

biggest problems in terms of the way

110:11

people view the world.

110:12

>> Yeah. I'm curious what you think like

110:14

you know like my my opinion is that it's

110:17

not good for the kids.

110:18

>> It's terrible for them.

110:20

>> Yeah. But I think they should have some

110:21

exposure to it because I think it's good

110:24

to know that it's a thing. And I think

110:26

children are fairly resilient and they

110:28

learn. But the anxiety levels of kids is

110:31

much higher than ever before. Suicidal

110:33

ideiation's higher, self harm.

110:36

>> Yeah.

110:36

>> Yeah. I'm a little my belief is that um

110:41

when you're just fed of feed

110:44

and and and and the algorithm of the

110:46

social media company decides what you're

110:47

going to see next, it it curbs your

110:50

curiosity.

110:51

And I I don't I don't think things that

110:54

curb human curiosity should be

110:56

encouraged.

110:58

>> Yeah, I agree. And so if the app is

111:00

designed in a way where it asks you what

111:03

you're interested in and helps you to

111:05

come up and find things that that are

111:08

very related to what you're interested

111:10

in,

111:10

>> right?

111:10

>> That's awesome. But that's not how it

111:12

works. It it's literally like it starts

111:14

with something, you start doom scrolling

111:16

and then start showing you what you just

111:18

scroll and then you end up in an echo

111:20

chamber. And and that's not that's not

111:22

necessarily good.

111:23

>> Well, you can get trapped. Yeah, you can

111:24

get I'm in a trap of schizophrenics

111:27

lately on Instagram, which is mostly

111:30

schizophrenics, like people that tell

111:32

they're the rightful president of the

111:33

United States and like you tell the guy

111:35

hasn't showered in days and you know,

111:38

and if you have a phone, you can create

111:40

an account and you just start uploading

111:42

nonsense and then for whatever reason,

111:44

I've watched a couple of them. So now

111:45

they just keep showing them to me

111:46

>> and it's full of AI slop right now. like

111:48

a lot of AI like it's not even clear

111:51

>> and it's not labeled also clearly

111:53

whether it's been made with AI or not so

111:56

often so essentially it's leading to a

111:59

complete loss in in in trust where when

112:01

I see something I don't even know if

112:03

it's real anymore

112:04

>> right and it's going to get worse

112:05

>> yeah it's going to get worse to the

112:07

extent that you're you're going to like

112:08

your default would be that this is AI

112:11

and then like you're going to have to go

112:14

through multiple layers to finally

112:15

verify if it was

112:18

Um and um and even like verified

112:22

accounts post a lot of AI stuff. So it's

112:23

not it's not about like whether the

112:25

account is verified by Meta or some or

112:27

or whatever, right? So I think um

112:31

fundamentally I I'm I I I feel like okay

112:33

the way I think about it is what are

112:36

pieces of technology if did not exist

112:39

uh would would be a really bad thing for

112:41

the world and what are pieces of

112:43

technology did not exist wouldn't even

112:45

matter. And and I feel like social media

112:48

is more towards a second.

112:50

>> Yeah.

112:51

>> Like you know uh searching for

112:54

information and answering questions and

112:56

like getting you know AIs to like do

112:59

things for you uh help you learn new

113:01

things faster all that stuff is some we

113:04

need more of that but um because it

113:06

supercharges our curiosity whereas like

113:09

brain rot feeds with AI slop doesn't

113:12

actually supercharge our curiosity. It

113:14

actually curbs our curiosity. And so if

113:17

we believe that if we believe in the

113:18

curiosity premium idea

113:21

uh we need to encourage things that

113:23

supercharge our curiosity and discourage

113:24

things that curb our curiosity.

113:27

Do you anticipate a time where we

113:30

recognize the dangers of algorithms and

113:33

there is some discussion to either curb

113:36

them or allow people to have control

113:39

over them in a real meaningful way like

113:41

you could dictate maybe through AI even

113:44

that there's an AI interface to your

113:46

algorithm that understands your

113:48

particular emotional needs your

113:50

curiosity like only show me this is what

113:53

I'm interested in carpentry and

113:54

basketball games show me those I don't

113:56

want I don't want to see who's getting

113:59

divorced. I don't give a about

114:00

this.

114:01

>> Yeah.

114:02

>> So, here's the thing. You can still

114:04

customize on most of these social apps.

114:08

You know, if you it'll be deeply buried

114:10

somewhere in the settings somewhere and

114:11

you can you can go and say stuff. But

114:14

the reason it's buried is because once

114:15

you you always have to say it or like

114:18

it's the starting entry point for your

114:20

experience there, your engagement time

114:22

would go down because once you consume

114:23

the content that you really want, you

114:25

you would go back to your work, which is

114:26

what you really need to be doing,

114:28

>> right?

114:28

>> But that doesn't help them sell more

114:30

ads,

114:30

>> right? And so the in incentives are not

114:33

align

114:35

and and so Elon has this really good

114:37

metric he talks about where it's like uh

114:40

total amount of unreged minutes spent on

114:43

the app should go up.

114:45

>> That's a good question.

114:45

>> It's hard to measure. It's hard to

114:47

measure.

114:48

>> It's more like a in spirit the right

114:51

metric.

114:52

>> But this metric is also why it's hard to

114:54

make money on ads if you care about this

114:56

metric. which is why X doesn't really

114:57

make a lot of money on ads compared to,

115:00

you know, Instagram or YouTube,

115:02

>> right?

115:02

>> Because uh you're kind of like

115:04

optimizing for interestingness like but

115:08

doesn't mean X has everything, right?

115:09

There's a lot of chaos, there's a lot of

115:11

memes, there's a lot of like um weird

115:13

going on there as well. But u in

115:16

general, social media is not necessarily

115:18

like great for people. I think it's

115:20

terrible for people, but it also

115:23

provides you with a way better

115:25

understanding of what's going on in the

115:28

world than has ever existed before.

115:30

>> X particularly

115:31

>> X particularly

115:32

>> because it's um it's a place for like

115:35

discourse. It's it's a textbased app

115:37

more than a video based app,

115:39

>> right? So um naturally like people tend

115:43

to engage in discussions and debates and

115:45

you know there's a lot of curious

115:46

debates going on there and a lot of

115:48

interesting viewpoints expressed by

115:49

people. So I think in terms of the

115:52

unreged minutes is actually one of the

115:54

better social media apps. But apps that

115:56

are purely based on like video or or or

116:00

images

116:02

and largely video these days I think

116:04

that's just you know just trying to get

116:06

your eyeballs in time.

116:07

>> Yeah. Those are the mind numbers. Yeah,

116:09

>> they just numb your mind.

116:10

>> I mean, it's depressing when you go into

116:12

a metro and you just see people just

116:13

scrolling through their feed. Nobody

116:16

>> Everybody doing it. You look the entire

116:18

car, everyone's doing it.

116:19

>> It's just insane.

116:20

>> Yeah. It's weird. Yeah.

116:22

>> I I always say that if there was a drug

116:23

that existed that made people stare at

116:24

their hand for six hours a day,

116:26

everybody would be like, "Get that out

116:27

of here."

116:28

>> But that's essentially what we're doing

116:30

cuz like most of what people are looking

116:31

at most of the time, they don't even

116:33

remember.

116:34

>> Yeah.

116:35

>> They're just scrolling through this

116:36

thing.

116:36

>> It's brain rot. It's brain rot. It it

116:38

curbs your curiosity.

116:39

>> Yeah.

116:39

>> I mean, Apple has these settings in

116:41

different apps. Have you Have you tried

116:42

this where you can set the timer for

116:46

every app?

116:46

>> No, I just use discipline. I don't I

116:49

don't engage very much anymore. I very I

116:52

I dip my toe into X every day for a few

116:56

seconds. I go, what's everybody mad at?

116:58

What's going on? Who stole this? Who how

117:01

much corruption's here? Who got killed

117:04

there? Okay, bye. And then I just check

117:06

out. I I don't want to do it.

117:09

>> And um Instagram to me is just nonsense.

117:12

It's I just look at that every now and

117:14

then for nonsense and occasionally

117:15

something interesting.

117:17

>> Really? YouTube is my main go-to thing.

117:19

Yeah.

117:19

>> Because YouTube is my most unreged

117:22

minutes.

117:22

>> Yeah.

117:22

>> YouTube for me is always interesting.

117:25

There's always like some cool thing on

117:28

Cosmology. There's some I watch fights

117:31

on YouTube. I watch professional pool

117:34

matches. That's what I do for the most

117:36

part. I that's where I really like find

117:38

my actual interests and fulfill my

117:40

curiosity.

117:41

>> Long form content is what human mind

117:44

should be trained to consume more of.

117:46

Whether it's books, whether it's like,

117:48

>> you know, like 30 minute videos

117:50

explaining something.

117:51

>> Mhm.

117:52

>> And and you you you need to train your

117:54

mind to actually complete it. That's

117:55

actually the biggest problem with the

117:56

younger generation. more they're in the

117:59

reals experience short form video.

118:02

>> Uh they're unable to actually like

118:04

complete like long videos anymore.

118:06

>> That's true. But also at the same time

118:08

the rise of podcast is happening.

118:11

>> Yeah.

118:12

>> And it's great. It's great.

118:13

>> So there's it's not it's not universal.

118:16

It's like there's a lot of people that

118:17

don't find fulfillment and all the doom

118:18

scrolling and all the nonsense and they

118:20

they really do want

118:21

>> Yeah. I'm I'm particularly just focused

118:23

on the younger generation. I'm sure like

118:26

people like us can adapt to like okay

118:27

let's say maybe I have a temporary

118:29

addiction to social apps and we can

118:31

>> but a lot of the young people are the

118:33

people like I meet kids like at the mall

118:35

that are 11 that listen to my podcast.

118:37

>> Really?

118:38

>> Yeah.

118:38

>> Wow.

118:39

>> I know it's nuts. They go I love your

118:41

podcast. I'm like who lets you listen?

118:43

Get out of here.

118:45

>> No, I'm always joking around about it.

118:47

Like it's really cool.

118:48

>> But no, there's a lot of like

118:50

particularly like young boys that come

118:52

up to me all the time that are

118:53

interested in it. That's amazing.

118:55

>> I love it. I love it because then

118:56

they're going to get exposed to some

118:58

interesting ideas and it'll also

119:00

encourage them to have those kind of

119:02

conversations with each other,

119:03

>> right?

119:04

>> Yeah.

119:05

>> Who Who's podcast do you listen to?

119:08

>> I love Tim Dylan's. He's probably my

119:10

favorite because it's the most accurate

119:13

and also satirical and hilarious view on

119:17

everything that's going on in the world

119:19

in terms of like war and world news and

119:23

culture And he's my favorite. He

119:26

was just on here yesterday. I

119:28

love that guy to death. He's so funny.

119:30

He's so crazy. It's like his mind works

119:33

in such a unique way and it's developed

119:36

cuz his podcast is different where he

119:38

very rarely has guests.

119:40

>> So most of the time it's just him

119:41

ranting and his producer laughing and

119:44

he's the best ranter that's ever lived.

119:45

I don't think there's anybody that's

119:46

even close. He's the goat. Like there's

119:49

like I don't think there's any argument.

119:51

Every comedian agrees like as far as

119:53

like just the ability to just sit in

119:55

front of a microphone and rant. Like

119:57

Bill Bird does it well. He's good at it.

119:59

There's a few other guys that are good

120:00

at it. No one's as good at it as Tim.

120:02

He's the most consistently entertaining.

120:05

And then for just mind, not mindless,

120:08

but like to escape. I listen to a lot of

120:11

archery shows and hunting shows where

120:14

they're talking about different tactics

120:16

in hunting or different

120:18

>> techniques in archery, new equipment,

120:20

and new innovations.

120:23

>> Archery is an interesting thing because

120:25

every year bow manufacturers make a

120:27

better bow.

120:29

and like tiny little engineering changes

120:33

of these bows. Like it's a weapon that's

120:36

been around for who knows how many

120:38

thousands of years. But what the

120:41

>> And you're able to feel those

120:42

improvements.

120:43

>> Oh yeah. Yeah. You feel the difference.

120:44

Every year Hoy put puts out a new bow

120:46

and every year I'm like, "Motherfucker,

120:48

they did it again. It's better." So just

120:51

tiny changes, less vibrations in the

120:54

hand, more balance in the shot, you

120:56

know, more forgiving in terms of uh

120:58

accuracy.

121:00

I love that stuff. So I get really

121:02

fascinated by engineering, really

121:03

fascinated by uh automotive engineering.

121:06

I'm really interested in like that's

121:08

another thing where like every year

121:10

people figure out how to make a car that

121:12

can hold more G's on a skid pad that can

121:15

get around a track quicker. Like every

121:17

year they're battling to see who can get

121:19

around the Nurburg Ring quicker. And

121:20

what are they doing? They're adding

121:22

horsepower, increasing suspension travel

121:24

and and uh suspension tuning rather and

121:27

making them more compliant or making

121:29

them stiffer and and making them more

121:31

adjustable and then like tire compounds

121:34

and I'm just interested in anything that

121:38

where someone's working on something and

121:40

getting better at something or getting

121:42

new information. I love history

121:44

podcasts. I listen to a bunch of history

121:46

podcasts.

121:47

>> So that's most of the time when I'm if

121:50

I'm listening to something, I either

121:51

want to be entertained or I want to be

121:53

educated.

121:53

>> Educational. Yeah.

121:54

>> Yeah.

121:55

>> Yeah.

121:56

>> And that's entertaining.

121:57

>> Yeah.

121:57

>> What about you? What kind of stuff do

121:59

you listen to?

121:59

>> I mean, I listen to your stuff. I listen

122:01

to Lex. There's this guy. Um I mean, you

122:04

know, you might you had him on like Rick

122:06

Rubin, of course.

122:06

>> Sure. Yeah. Love that guy.

122:08

>> Yeah. Yeah. He's he's awesome. I listen

122:10

to his stuff. Um and um I mean I also

122:14

watch like some interesting videos about

122:17

you know concepts I don't understand.

122:20

There is this YouTube channel

122:21

Veritasium. You should check it out.

122:24

>> What is it called?

122:24

>> Veritasium.

122:26

>> How do you spell that?

122:27

>> V E R I T A S E U M. Veritasium.

122:33

>> What does it mean?

122:34

>> Um I think

122:34

>> is that someone's name?

122:36

>> No. Veritas just means like seeking

122:38

truth kind of thing.

122:39

>> Oh. Um, is it this channel 20 million

122:42

subscribers?

122:42

>> Yeah. Yeah.

122:44

>> Okay.

122:45

>> 20.9 million subscribers.

122:47

>> Obviously, a lot of people agree.

122:49

>> So, they make all these very interesting

122:51

videos about like um stuff that, you

122:54

know, you would be curious about, but

122:56

you never actually bothered to ask that

122:58

or learn more about and um explain some

123:01

of the most underderstood companies

123:05

u or like phenomena.

123:07

And um I just love watching it, you

123:10

know. I'm I'm This is kind of like my

123:11

idea of doom scrolling. Like I like I

123:13

like watching like 20 videos at once.

123:15

>> Yeah, I am going to subscribe to it

123:17

right now.

123:18

>> It's pretty cool.

123:20

>> Veritassium.

123:23

There it is. Got it. Subscribed. Bam.

123:27

>> And explains all these like fun concepts

123:30

that are, you know, you take it for

123:33

granted like, okay, why is Google Maps

123:34

really fast? Like, okay, it'll tell you

123:37

what's going on, how the data is used

123:39

across so many different people at once

123:40

and all these different

123:42

>> CIA's new tech doesn't make sense.

123:44

Exactly.

123:46

>> We were just talking about that

123:47

yesterday. We were doubting it. You

123:49

know, the heart murmur thing, do you

123:50

know about that?

123:51

>> No. So, the pilots that were downed in

123:54

uh Iran,

123:56

>> they said that they have this technology

123:59

that allows them, I think they could use

124:01

it up to 70 miles and they can detect a

124:04

very unique heart rate. Like your heart

124:07

rate is different than my heart rate.

124:08

They could know it's you. You could be

124:10

hiding in the mountains and they could

124:11

find you from 70 miles away with this

124:13

technology.

124:14

>> Wow.

124:15

>> A lot of people like

124:16

>> beams or waves or something.

124:18

>> Well, it's called what is it called?

124:20

Quantum magnetometry. Is that what they

124:22

call it?

124:24

I think that's what it was. Remember we

124:25

looked it up yesterday. I think they're

124:28

using the word quantum and not

124:29

explaining what they're doing, like how

124:31

they're doing it. And you're like,

124:33

"Okay, is that real or is this some

124:36

invented horseshit to cover the fact

124:39

that they have some very sophisticated

124:41

satellite imagery where they can have a

124:43

a detailed map of literally the entire

124:46

surface of the world. They know exactly

124:47

where people are, but they don't want

124:48

our enemies to know that they have this

124:50

capability. So, they're making up

124:52

something.

124:53

>> I see.

124:53

>> That was my suggestion yesterday that

124:56

like maybe they're full of cuz the

124:58

whole thing seems nuts. What is it

124:59

called?

125:00

>> You got it.

125:01

>> Is it's quantum magnetometry.

125:03

>> Sure.

125:03

>> Okay. What does that mean? You tell me.

125:05

>> I don't know

125:05

>> exactly. Yeah. So, this guy, he's saying

125:09

it doesn't make sense. Yeah. And a lot

125:10

of people say it doesn't make sense.

125:12

Like it doesn't seem to vibe with

125:14

anything that we know that we can do.

125:15

magnettometry. Yeah.

125:16

>> Yeah.

125:17

>> First time hearing it.

125:18

>> See the pull up the decry this

125:20

description the uh official description

125:22

of what this stuff is capable of. So

125:24

this is supposedly some very advanced

125:27

CIA tech that allowed them to locate

125:30

this down pilot.

125:32

>> Interesting.

125:34

>> Maybe. Or maybe there's something else

125:36

going on. Or maybe there's some other

125:37

methods that they use that they don't

125:39

want the enemy to know about. Maybe some

125:42

beacon these guys have on them. Yeah. I

125:44

guess what's the incentive for CIA to

125:46

actually describe how their technology

125:48

works?

125:48

>> Yeah. Zero.

125:49

>> Why would they tell you that?

125:50

>> Yeah.

125:51

>> Why would they tell you they even have

125:52

that? That's crazy.

125:53

>> Yeah.

125:54

>> And then Jamie had a good point.

125:55

>> The capability is insane. Detecting your

125:58

heart rate 70 miles away is just how

126:00

insane.

126:01

>> Yeah. How? And the when they throw the

126:03

word quantum in things, I was h what

126:05

happened with that White House

126:07

announcement. Sorry, I keep

126:09

>> the quantum computing.

126:10

>> Yeah. the the remember there's Q news

126:13

coming soon and then they like at the

126:15

bottom Q sounds for quantum.

126:18

>> Oh, I see.

126:18

>> Is that what it is?

126:19

>> I thought they just announced a bunch of

126:21

investments in a bunch of quantum

126:22

companies.

126:22

>> Maybe that's it.

126:23

>> Taking a Yeah, IBM was getting some

126:26

funding or whatever.

126:28

>> So, uh this quantum magnetometry, can

126:31

you uh pull up a description of what it

126:33

is?

126:33

>> Sorry, I started looking up the

126:34

>> Sorry, I know I was asking you too many

126:36

questions at the same time. Quantum

126:38

sensor help rescuers.

126:41

>> Yeah. So this is it.

126:42

>> Ghost murmur.

126:44

>> Yes, that's what it's called.

126:46

>> Purported surveillance technology

126:47

utilizes long range quantum

126:50

magnetometry. What is that? Quantum

126:52

magnetometers measure extremely faint

126:55

magnetic fields including the body's

126:56

natural electromagnetic signals by

126:59

tracking changes in the energy states of

127:01

atoms or subatomic particles. What

127:05

technology reportedly uses microscopic

127:07

defects in synthetic diamonds. When

127:10

illuminated by a laser, these centers

127:12

are hyper sensitive to tiny magnetic

127:14

fluctuations.

127:16

>> The heart signal, while human heartbeats

127:18

produce a magnetic field, is extremely

127:20

weak around 50 to 100 pico teslas and

127:24

typically degrades over very short

127:26

distances. So the G ghost murmur

127:29

deployment, they reportedly used Ghost

127:32

Murmmer during a mission in southern

127:33

Iran to pinpoint the location of a down

127:35

American airman using uh hiding rather

127:38

in dense mountainous terrain by mounting

127:41

these quantum sensors into a helicopter.

127:43

The system purportedly registered the

127:45

pilot's heartbeat from afar.

127:49

Okay, does that sound like horshit? I

127:52

mean, not it doesn't sound full of

127:53

but like basically the part that sounds

127:56

surprising to me is how they're able to

127:58

deal with all this like distance and

128:00

attenuation across the distance,

128:02

>> right?

128:02

>> And all this interference and they claim

128:04

to use AI for that, but nothing is

128:06

really described on how they use it,

128:08

>> right? So, if they're not describing how

128:10

they use it, why are they even telling

128:11

us they have it?

128:12

>> Why?

128:13

>> So, like there there's a lot of

128:14

skepticism on it.

128:16

>> Yeah. Laws of physics. Physicists point

128:18

out that the heart's magnetic field is a

128:21

million times weaker than the Earth's.

128:23

Detecting it at a range of miles rather

128:25

than centimeters defies currently

128:27

published peer-reviewed physics.

128:30

Alternative explanations suspect that

128:33

while quantum sensors were likely on

128:35

board, they were probably tracking the

128:36

radio waves of a survival beacon, the

128:39

metal in the pirate pilot's equipment or

128:42

using traditional thermal, infrared, and

128:44

radar capabilities rather than detecting

128:46

a raw heartbeat via magnetic fields. I

128:48

as I do remember seeing a different part

128:51

of a when that story happened back in

128:53

April. Someone did report on like one of

128:55

the military websites that there was a

128:57

survival beacon that they used to track

128:58

them

128:59

>> and that the whole quantum member stuff

129:01

is like nonsense.

129:02

>> Yeah, I saw that too.

129:03

>> No one wants to report that cuz it's not

129:05

fun,

129:05

>> right?

129:06

>> No, the ghost murmur thing is awesome

129:08

fun. And if that is real, like boy,

129:12

>> you can imagine a world a 100 years from

129:14

now where that is real. So, it's

129:16

exciting.

129:16

>> Oh, yeah. 100 years is a long time for

129:17

this to be real.

129:18

>> Yeah. 100 years they probably got it

129:20

down pat. Then that's the problem. You

129:23

can't hide from the robot dogs from

129:25

black mirror.

129:26

>> Yeah.

129:26

>> You know.

129:29

>> Yeah.

129:30

>> Do you ever while you're working in AI,

129:32

do you ever wonder like

129:35

is this the downfall of humanity? Is

129:37

this a good thing to be worked on? Did

129:39

you ever have like doom moments?

129:41

um not on specific things I'm working

129:44

on, but in general um I do worry about

129:48

like how much you know you you you

129:51

obviously want to like stay in charge

129:53

and you know be in control of your

129:55

experience. Um still be the one driving

129:59

change and have a lot of agency for

130:01

yourself. So I do worry that like it's

130:03

all about like making sure everybody's

130:05

upskilled and understanding like where

130:07

the future is headed and not being like

130:10

um

130:12

fed only like dangerous apocalyptic

130:14

messages and uh because it's very

130:17

essential that human beings retain their

130:19

agency and staying curious, right? Like

130:21

so if if that stops being the case, if

130:23

you start subscribing to the vision that

130:25

okay, your jobs are done, you don't

130:27

really have any meaning in the world and

130:28

we'll pay you some dividends and you

130:29

just sit at home and chill, that is that

130:32

is not a good thing. So and and and I

130:35

feel like there are not enough voices in

130:36

AI that are actually saying anything

130:38

different to that. And I like like when

130:41

Jensen was here, I think he was a little

130:42

different. I think he tried to give a

130:45

more positive

130:47

uh version where he said okay like the

130:50

the radiologist thing if okay all

130:52

radiologists can take away you know they

130:54

start doing different kind of work so I

130:57

think we need to start looking at like

130:59

okay like okay first of all guys relax

131:01

you have a lot of you have one premium

131:03

skill your curiosity so let's figure out

131:06

ways to channelize that let's change the

131:07

way work is done at companies let's

131:09

change the way educational institutions

131:10

run let's change the incentive structure

131:12

structures and and let's help you build

131:15

new ideas on new companies and explore

131:18

things that are not even being

131:19

considered and the government should

131:21

obviously like you know support all

131:22

these initiatives. So that's what needs

131:24

to happen more. But what's happening

131:26

actually right now is um okay like hey

131:30

guys you're all losers. You're going to

131:31

lose your jobs and and and don't blame

131:33

me

131:34

>> because I'm I told you so. Right.

131:37

>> And um and and and and still give us

131:40

money because we're still going to do it

131:41

anyway. And so that that's what's

131:43

happening more and I think uh we should

131:45

stop doing that. That that's my opinion.

131:48

Well, it is. The problem is it's kind of

131:50

a self-fulfilling prophecy. And if you

131:51

tell people that they're going to be a

131:53

loser and you're going to their life is

131:55

over, they're going to think that way

131:56

instead of giving them an understanding

131:58

of like, look, this can open up new

132:00

doors for you. This can

132:01

>> and anytime there's any sort of

132:03

disruptive technology, there's always

132:04

the the fear that it's going to go

132:06

badly. Yeah.

132:07

>> This was the case with

132:09

>> the locomotive. This was the case with

132:11

uh when the printing press was invented.

132:14

>> Yeah. By the way, like I I I I did some

132:17

research on this where um and the

132:19

industrial revolution happened. Um

132:22

people got new ideas. Um okay, like for

132:25

example u when the industrial revolution

132:27

happened um who came up with the idea of

132:30

a steel plow John Deere. Until then we

132:33

were using wooden plows to like for

132:35

farming. No farmer complained that hey

132:38

like we need fewer farmers now because

132:41

steel plow is able to do it more

132:42

effectively. No one complained. You

132:45

actually had more farms and more

132:46

productivity, more crop yields, and

132:48

you're happier.

132:50

>> But isn't that just a regular tool as

132:52

opposed to AI?

132:53

>> Sure, AI AI is different. It's not

132:56

overnight going to become something

132:58

that's capable of just running an entire

133:01

multi-trillion dollar company on its

133:03

own. There are a lot of things that AIs

133:05

cannot do. There's a lot of tacid

133:06

knowledge in every company that AIS

133:09

don't quite understand. And there's a

133:10

lot of new directions that you can just

133:12

start working on that AI are not well

133:15

equipped to do because it doesn't have

133:16

full knowledge about it and the

133:17

knowledge about it is yet to be captured

133:19

and some of that requires like humanto

133:21

human work and collaboration.

133:23

So we obviously have to gravitate

133:25

towards what is scarce. When AI makes

133:28

the current labor that's considered

133:30

scarce because that's where the money is

133:32

going in commodity then we have to

133:35

gravitate towards what is scarce and the

133:38

only way to do that is to seek things

133:40

that we don't know about which is only

133:44

something we can discover through our

133:46

curiosity. There's nothing else.

133:48

Whatever we don't quite understand well,

133:50

whatever we don't know how to do well

133:52

yet, even with the current capabilities

133:54

of AI, uh that's where we should pull

133:57

our labor and workforce into. So, it

133:59

needs more responsible messaging

134:02

and that's not quite happening right

134:04

now. I think it needs responsible

134:06

messaging and then in the future what it

134:08

needs is like real direction in terms of

134:12

like letting people find their curiosity

134:15

and find these paths of interest and

134:18

find something to do with themselves

134:20

>> that doesn't involve whatever their

134:23

previous occupation that's irrelevant

134:25

now.

134:26

>> Mhm. That's true.

134:28

I think like passion for people is

134:30

something that not a lot of people would

134:32

be able to answer out of the out of the

134:34

box. Like if you go and ask them what is

134:36

your real passion and and and and the

134:38

only thing they have known in life is to

134:40

just climb up career ladders and make

134:42

more money.

134:43

>> That's going to actually take them a

134:44

while to even discover.

134:47

>> And um

134:48

>> which is why it's so important to get

134:49

kids off on the right start.

134:51

>> Yeah. That's that's the hope. That's

134:52

that's our hope for the future is the

134:54

kids the kids are born curious. they

134:57

don't need to change themselves to be

134:59

curious,

134:59

>> right?

135:00

>> The adults who probably already are like

135:02

because of this knowledge work thing

135:05

um who kind of curb their curiosity and

135:07

try to fit into the existing system, it

135:10

might be a little hard for them to

135:11

adapt. But the kids, I think they don't

135:13

have this problem. So I'm I'm actually

135:16

optimistic about the future long term

135:18

because the future is all centered

135:19

around like whoever is like very young

135:21

today. What do you think about this idea

135:24

that universal basic income is going to

135:26

be required?

135:28

>> Some form of it is good. Some it's like

135:30

a dividend. I almost think of it as a

135:32

dividend. If a lot of spend that most

135:36

companies are currently doing today on

135:38

like payroll, which is paying a

135:40

knowledge worker for a certain task.

135:42

Think of knowledge work is basically

135:44

taking information and transforming it

135:46

into an artifact,

135:48

right? And it's it's messy and

135:50

complicated. Let's assume that's being

135:51

done by AIS. So obviously companies will

135:54

start spending more on compute instead

135:56

of payroll. It's just a reallocation of

135:59

like spend or budget similar to like

136:01

what happened in advertising industries

136:03

where most of your advertising budgets

136:05

went to like television and like

136:07

billboards and then now it's starting to

136:09

go to Google and Instagram and YouTube

136:10

and all that. So um

136:14

when that happens um obviously like the

136:18

AI companies are going to make a lot of

136:19

money

136:20

and uh people who helped be part of

136:23

creating it or like either directly or

136:25

indirectly would want to have some role

136:28

to play in that ecosystem

136:31

and a good way to involve them is

136:32

through giving them some ownership in

136:34

the company. So as shareholders you if

136:37

you get dividends from the profits

136:38

generated by the AIS it's not a bad

136:41

thing but but that's that shouldn't be

136:43

the only thing

136:44

>> right so this is similar to like people

136:46

that live in Alaska they get a check

136:48

because

136:48

>> correct

136:48

>> Alaska Alaska get Alaska does this and

136:51

it's not a bad thing as long as they are

136:54

doing some other things

136:55

>> right

136:56

>> alongside

136:57

>> it could lessen the burden

136:59

>> correct

137:00

>> yeah and and and if people are

137:02

interested in still being part of the AI

137:03

industries they go do things that AIs

137:05

are not able to do today. And that's

137:08

that's been the case before like when

137:09

industrial revolution started um the the

137:12

United Kingdom actually started like

137:15

like projects around building railroads

137:18

and that gave a lot of people who are in

137:20

the cottage industries new jobs.

137:23

So there are going to be a lot of new

137:24

projects to just okay like what if we

137:27

want to reimagine the government itself

137:28

where the government runs largely on AI.

137:31

>> Yeah was that was my next question.

137:33

>> Yeah. So then we need people for that.

137:35

>> Yeah.

137:36

>> Because this is a legacy industry. It's

137:37

not it's not about the capabilities not

137:39

being there. It's about working through

137:42

the legacy and bureaucracy to like

137:45

actually deploy and implement this

137:47

inside the most like like largest

137:50

institutions in the country and uh

137:52

that's going to need a new set of

137:55

skilled workers to go do that. So some

137:57

people who might be working at Microsoft

137:59

or something today might actually end up

138:00

working for the United States government

138:03

because uh Microsoft may not need them

138:06

especially for like you know internally

138:08

deploying AI or selling AI to their

138:09

customers but the government needs them

138:11

and and and if the government can pay

138:12

them well and it's a fulfilling job to

138:15

find some meaning for like doing

138:16

something good for the country it's not

138:18

a bad thing. So I I I think like just

138:21

like in the industrial revolution where

138:22

we had new projects because the demand

138:25

for AI was so big, we're going to start

138:27

seeing some new projects being created

138:29

in AI as well when the capabilities

138:31

advance enough that they can replace

138:32

knowledge workers.

138:34

>> That's the rosy scenario.

138:37

>> It's not as rosy like real world is

138:39

messy. A lot of things are still done

138:42

through trusting other human beings.

138:44

Nobody's like blindly trusting AIs. AI

138:47

still make a lot of mistakes. I know a

138:49

lot of people are hesitant to the idea

138:50

of AI running government and I get it.

138:53

But also look at what the people are

138:55

doing. Look at how much corruption there

138:57

is, how much fraud and waste. Imagine if

138:59

all fraud, waste, and corruption was

139:02

instantaneously eliminated.

139:04

>> Yeah.

139:05

>> I mean, that was what Elon tried to do

139:07

with Doge, right?

139:07

>> Right.

139:08

>> And and then I think the bottleneck

139:10

there was just discovering how slow it

139:12

is to do things. It's not he's not used

139:15

to running that slow.

139:16

>> Yeah. Yeah. And uh

139:17

>> also how much resistance because there

139:19

was so much grift.

139:20

>> Correct. Yeah. So

139:23

>> honestly like more than AI the

139:26

government is running a lot of legacy

139:28

software stack because a lot of these

139:30

legacy enterprise companies just have

139:33

created these multi-deade or like year

139:36

contracts that are hard to get out of.

139:38

And the way they do that is to sell it

139:40

at a much larger discount. And like you

139:43

know like if you're on on like a

139:44

specific OS, you're not allowed to

139:46

change this for like 10 years. You have

139:48

to use the same set of software. All

139:50

this uh people you hired only know to

139:52

use that tool. So it takes time to

139:55

actually change and implement new

139:56

things. Leave alone AI. Just if you just

139:58

wanted to like move everybody from

140:00

Windows machines to like Mac machines,

140:02

good luck with that. It's going to take

140:04

a lot of time. That's the state of the

140:07

the system. And so that has nothing to

140:10

do with technology. And so to do things

140:13

in such messy systems, you still need

140:15

people. You still need people to

140:18

navigate all these changes.

140:21

Um it's not about the capability of

140:23

technology. It's more about how the

140:24

system is structured. And that's why I

140:27

still feel there will be new jobs that

140:30

maybe the you know there's a lot of new

140:32

projects to be done. Maybe some good

140:33

leader actually wants to change the

140:35

system and is willing to be patient

140:37

about it. like you know over a 5 to 10

140:39

year horizon if you take 10 years to

140:41

actually like run majority of the

140:43

government processes on AIS it may seem

140:46

slow to you today but in the grand

140:48

scheme of things it's actually good for

140:49

the country

140:51

and that's still going to need a lot of

140:53

nice engineers to go work on these

140:55

projects so they're not going to lose

140:58

all their jobs there's going to be some

140:59

displacement there's going to be some

141:00

new projects there's going to be new

141:01

priorities but it'll it'll keep going

141:04

the system will keep going because

141:06

that's just how historically things have

141:09

When you think about the future of AI

141:11

and you think of this

141:14

>> the so when you think about AGI in

141:16

particular you think about something

141:19

that could potentially make better

141:21

versions of itself

141:23

>> self-replicating

141:24

>> yeah and then how far does it go like

141:27

>> yeah so that is the uh that is the

141:29

ultimate form of I think some people in

141:32

Silicon Valley have started calling that

141:34

as ASI so when you see the word ASI I

141:37

being thrown around like people kind of

141:40

think of ASI as an AGI that can

141:43

recursively self-improve itself. So

141:45

that's going to be un going to be no

141:47

limits to how smart it can get,

141:49

>> right?

141:50

>> And um

141:52

I used to think that ASI is bottlenecked

141:55

by power because you need a ton of

141:58

compute for this model to keep on

142:00

training itself and running its own

142:03

rollouts and collecting data and then

142:04

going and updating itself.

142:07

But you could imagine that once the

142:08

algorithm is correct, the ASI could be

142:11

tasked with just making itself more

142:13

efficient to where improvement doesn't

142:15

just mean capability improvement.

142:17

Improvement could also mean power

142:18

efficiency

142:20

and um that way the as recursive safe

142:23

ASI that is improving itself also makes

142:26

itself more compact and more efficient

142:28

and it can run on less compute. So that

142:30

would be the ultimate project in AI.

142:32

Think of it as almost as the last

142:34

project in AI is basically cracking

142:36

recursive self-improvement. Once you

142:38

crack that, you don't have anything else

142:39

to work on. Um in practice, I think

142:42

what's going to happen is um because

142:45

information is so muddled and fragmented

142:47

and living in disjoint systems just the

142:50

way we have constructed our messy real

142:52

world. It's going to be hard to point

142:54

even a recursively self-improving AI at

142:56

some metric and say go improve this or

142:58

like go reduce inflation by 5%.

143:01

That would be awesome if you can task an

143:03

AI to do that. If that's the job of the

143:05

government to just reduce inflation,

143:07

have a deflationary effect on society

143:10

and make make goods and services a lot

143:12

more abundant and efficient.

143:14

It's going to have to deal with a lot of

143:16

messy legacy systems. If the task is to

143:19

go improve the health care, we're good

143:21

luck. Like who's going to deal with all

143:23

the compliance of actually implementing

143:25

these changes inside hospitals?

143:28

Most hospitals are still using legacy

143:30

software because that's the the software

143:32

provider has lobbyed the government in a

143:35

way where only they're allowed to do

143:36

that.

143:37

>> God, what a stupid bottleneck.

143:39

>> Exactly. So, a lot of the bottlenecks in

143:41

in in in actually having AIS just take

143:44

over and massively improve the human

143:46

society and our hospitals, our legal

143:49

systems, our government systems where

143:52

most of the payroll is going into. is

143:54

just bottlenecked by a lot of compliance

143:56

and regulation. And so that's why I feel

144:00

we human beings are still necessary to

144:02

effect the change

144:04

because these laws and and and

144:06

regulations were built for us.

144:08

>> And it also seems like we have to demand

144:09

that those systems be usurped.

144:12

>> Sure. 100%. And we need the help of AIS

144:15

to rewrite all these laws.

144:16

>> It's going to be humanly impossible to

144:18

go and change

144:20

one specific line here and there,

144:22

>> right? And then you're going to have a

144:23

bunch of these software companies that

144:24

are lobbying to try to stop that from

144:26

happening. And yeah,

144:27

>> it's it's that's why like this messiness

144:31

and this need for getting all people on

144:33

the same page and actually steering the

144:34

society in a positive way. Our jobs will

144:37

probably be more steered towards that

144:39

problem solving at a different level of

144:42

abstraction. maybe more need for EQ,

144:45

more need for actually like

144:47

understanding differences of opinion and

144:49

still like a leadership quality, ability

144:53

to understand people and ability to

144:56

convince people. These these these are

144:58

the skills that and will be even more

145:00

important in a world where like actual

145:02

work can be done by AIS but affecting

145:05

the change in in our society in our

145:09

country still needs human beings because

145:11

the systems are messy.

145:15

>> It's a weird world we're in right now.

145:17

>> Yeah.

145:18

>> It's never been weirder. That said,

145:20

there's a lot of things that that can

145:21

still go wrong when you give power so

145:24

much power to u you know like specific

145:28

companies and uh they deploy all these

145:30

bots and then um anybody can use them in

145:34

weird ways. You don't even know if like

145:36

you're talking to a real person anymore,

145:38

>> right?

145:39

>> They're like people who just run AI

145:41

responses and chat with like 500 people

145:43

at once and that's like a whole

145:45

business. And so, um, I think it's it's

145:49

gonna it's going to take a lot of

145:51

adjustment.

145:52

>> Well, the another piece of adjustment

145:54

that a lot of people are coming to grips

145:55

with is that this is a new part of our

145:57

conversation. And that in 2020, like

146:00

when I first moved here, AI was never

146:02

discussed.

146:03

>> It was not a thing.

146:04

>> Yeah.

146:04

>> I mean, we knew about it. We knew about

146:06

AI, but it wasn't like you it wasn't

146:09

>> a huge part of the cultural discussion

146:12

of what the future holds for us.

146:14

>> And now it is. Now, It is central. Yeah.

146:17

>> And in that short amount of time in just

146:19

six years, it really makes you wonder

146:21

because we know how technology

146:24

progresses exponentially like what it's

146:26

going to look like 6 years from now.

146:27

>> Yeah. The 2028 like like you're

146:31

definitely my prediction is 2028

146:32

election debates are going to be largely

146:34

about AI.

146:35

>> Wow.

146:36

>> Yeah. AI energy crisis the power power

146:43

people are going to care about all these

146:44

things.

146:46

because it AI is no longer a thing that

146:49

is new. It's part of all our lives.

146:51

Everyone's using some form of AI in in

146:53

some ways and uh it's not as dangerous

146:57

as people thought. It's it's it's an

146:59

amazing tool for like doing work and

147:00

asking questions and learning things and

147:02

all these things

147:03

>> when used correctly.

147:04

>> Yeah.

147:05

>> Yeah.

147:05

>> Can also be used incorrectly. Uh

147:08

>> like everything

147:09

>> like everything. So it's far more

147:11

powerful that incorrect usage can cause

147:13

serious damage like like for example

147:16

people kids who are using AIS for like

147:19

companionship

147:20

>> right

147:21

>> crazy things are happening there crazy

147:23

things are happening

147:23

>> not good

147:24

>> yeah it's it's even it's it's as

147:26

dangerous as

147:27

>> or probably more dangerous than social

147:28

media

147:30

>> and uh it's also scary that social media

147:32

companies want to build more of these

147:34

kind of like companionship apps because

147:37

they know that okay their only job was

147:39

to get you engaged more and that's the

147:42

only way to sell more ads and make more

147:44

money. And clearly companionship is a

147:46

way to get you engaged more.

147:48

>> Yeah.

147:49

>> And so that's dangerous. If if ads start

147:51

being part of like AI chats.

147:55

>> Yeah.

147:56

>> Because then if that that ends up

147:57

working then all these chat bots are

148:00

just going to be secants that just tell

148:04

you stuff that you you you want to hear.

148:06

It's also it's an indistinguishable

148:08

indistinguishable faximile to a real

148:10

person. Like they communicate like a

148:12

real person, right?

148:13

>> So you really think you have a

148:14

relationship with this,

148:16

>> right? And and and and it it truly um

148:19

screws with your mind. It's hard to like

148:21

decouple and like it takes a lot of time

148:23

to recover if you want to like you know

148:26

unplug and um so the business model

148:29

incentives are not well aligned to

148:31

humanity. Did you see that um AI

148:34

companion that they developed that was

148:36

at the Consumer Electronic Show in Vegas

148:38

this year?

148:39

>> Which one?

148:40

>> It's like a hot Asian lady.

148:42

>> I see. Yeah. Yeah. These are these are

148:44

the weird kind of projects that are

148:45

going on.

148:46

>> Yeah. It's a hot Asian lady that talks

148:48

to you.

148:49

>> Yeah.

148:49

>> And you know, she talks to you through

148:51

AI. And right now it's just a kind of a

148:54

crude sort of robot. But

148:56

>> yeah,

148:56

>> you could see where it's going.

148:57

>> You can see where it's going.

148:58

>> X Machina.

148:59

>> Yeah. It's going

149:01

>> Yeah.

149:01

>> Right there.

149:02

>> Yeah. Yeah. That movie was

149:04

>> amazing.

149:05

>> Quite far ahead of it time.

149:06

>> Really?

149:07

>> Yeah.

149:07

>> That was It's one of my top 10 favorite

149:09

movies of all time.

149:10

>> It's underrated actually because people

149:12

like reviews on online say it's not as

149:14

good, but I liked it. I

149:16

>> I loved it.

149:17

>> I thought it was fantastic.

149:18

>> I like it better than her.

149:20

>> Yeah, her I lost her after a while. I

149:22

shut it off.

149:24

>> It lost my attention. I'm sure it's

149:26

good. It was the wrong time for me to

149:28

watch it.

149:28

>> But X Machin, I've seen it like five

149:30

times. I love that movie.

149:33

>> It's just so

149:34

>> I don't want to give anything away, but

149:36

it's it's so incredible and so bleak and

149:38

so

149:39

>> Yeah.

149:40

>> in the relationship that he has with the

149:42

the hot one.

149:43

>> Yeah. Yeah.

149:44

>> You believe it. You're like, I

149:46

>> I'd be right there with him. You know,

149:48

it's too confusing to our system to have

149:50

something that looks exactly like the

149:52

thing that you desire that is actually

149:53

interested in you. It just happens to be

149:56

all your data about stuff.

149:57

>> Yeah. Knows too much about you. Knows

149:59

how to pull your strings.

150:00

>> Yeah.

150:00

>> Yeah.

150:01

>> But listen, man, very fascinating

150:03

discussion. I'm glad we did it. Thank

150:05

you very much.

150:05

>> Thank you so much.

150:06

>> And thanks for having an awesome

150:07

platform. Perplexity has been great. We

150:09

really love using it here at the show.

150:11

It's It's made the show more

150:12

interesting. It's cool.

150:14

>> Thank you. It's very fulfilling because

150:15

like we we want the app to be used by

150:17

curious people like that. Like we want

150:19

to lift the ceiling of what our our our

150:23

population can be, you know? Not

150:26

everyone is like fully curious all the

150:27

time, but we're all born with it. So, at

150:30

some point in time, the system curbs it

150:31

from us. So, there should be more apps

150:34

that get us back to what we're naturally

150:35

good at.

150:36

>> Yeah, it's a fascinating tool for

150:37

technology or for curiosity rather

150:39

because

150:40

>> to be able and it's seamless the way we

150:43

use it on the show cuz there's always a

150:45

question. Yeah, there's always it comes

150:46

up so often like throw it in perplexity.

150:49

Let's find out what's up.

150:50

>> It's always been great for us. So, thank

150:51

you.

150:52

>> Thank you so much.

150:53

>> All right. My pleasure. Bye everybody.

Interactive Summary

In this episode of the Joe Rogan Experience, Joe Rogan and his guest discuss the fascinating parallels between modern advanced technology and the descriptions found in ancient Indian epics like the Mahabharata. They explore the idea that human history might be a cyclical progression of rise and fall, rather than a linear evolution. The conversation transitions into the importance of human curiosity as a driver of progress, the potential for AI to serve as a tool to supercharge that curiosity, and the complex ethical considerations surrounding AI, censorship, and the future of human society.

Suggested questions

4 ready-made prompts