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On The Lost Art of Watching Movies | Cal Newport

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On The Lost Art of Watching Movies | Cal Newport

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2027 segments

0:00

Late last month, The Atlantic ran an

0:02

article titled The Film Students Who Can

0:05

No Longer Sit Through Films. I want to

0:08

read you an excerpt from early in the

0:10

article. This excerpt starts with a

0:12

quote from a film professor. I used to

0:15

think if homework is watching a movie,

0:17

that is the best homework ever, Craig

0:19

Eperling, a film professor at the

0:21

University of Wisconsin at Matson told

0:22

me, but students will not do it. I heard

0:25

similar observations from 20 film

0:27

studies professors around the country.

0:29

They told me that over the past decade

0:30

and protect part particularly since the

0:32

pandemic, students have struggled to pay

0:34

attention to featurelength films. All

0:38

right. So, yeah, that's not great. But

0:39

here's the thing. I think there is both

0:42

bad news and good news here. The bad

0:45

news is, as I'll argue, this phenomenon

0:48

reveals the impact of digital technology

0:50

on our basic human ability to pay

0:52

attention and think is perhaps worse

0:54

than we originally imagined. But the

0:56

good news is that in this problem, we

1:00

can find its own solution. So, as I'm

1:03

going to go on to argue, getting better

1:06

at watching movies might just be the

1:09

right first step toward reclaiming your

1:12

brain. So, here's the plan. I'm going to

1:15

elaborate on those two arguments, right?

1:16

That our struggles to watch movie is a

1:18

side effect of digital technology and

1:20

that practicing watching movies can help

1:22

us reverse that damage. And then

1:23

assuming that you buy those arguments,

1:26

I'm going to get practical. I'm going to

1:28

give you specific advice for how to

1:30

become a better movie watcher, including

1:33

a list of classic movies that you should

1:37

start with. Jesse, I think it'll come as

1:38

no surprise that my main recommendation

1:40

is going to be conducting an extensive

1:43

scene by scene analysis of the 2002

1:45

Britney Spears movie Crossroads.

1:49

>> No, I like it.

1:50

>> All right. Too soon. All right. Uh then

1:52

we'll move on to my news and note

1:53

segment where uh by popular demand, I'm

1:55

going to take a close look at last

1:58

week's viral essay sensation. This is

2:00

Matt Schumer's essay, something big is

2:03

happening. It's one of these uh AI is

2:05

about to change everything for real this

2:06

time type essay. So we'll get into that.

2:08

We have a reader email about the

2:10

Olympics and we'll talk about my new

2:11

book. So we have a lot to get to. As

2:13

always, I'm Cal Newport and this is Deep

2:17

Questions, the show about the fight for

2:18

depth in an increasingly distracted

2:21

world. And we'll get started right after

2:24

the music.

2:34

All right. Right. So, to start our

2:35

investigation here, let's look a little

2:37

bit closer at this problem

2:40

of people having a hard time watching

2:43

entire movies. It's not just film

2:45

students and it's not just the people

2:46

that The Atlantic talk about. If you

2:48

start poking around on the internet, you

2:50

can find a lot of evidence of people

2:52

having the same issue. Um, I was looking

2:54

on the R movies subreddit and I found a

2:58

bunch of people on there who are giving

2:59

similar complaints. Let me read you a

3:00

quote here. This comes from a a Reddit

3:02

post. This might just be me, but for a

3:06

while now, I'm struggling to decide

3:07

which movie is worthy of watching, then

3:09

actually sitting and watching it. I can

3:11

watch it in the movie theater, but for

3:12

some reason, I just can't watch it at

3:13

home. I end up watching Seinfeld reruns

3:16

on TV. I don't know what's wrong with

3:17

me. All right, here's another quote from

3:19

another post from the movie subreddit.

3:22

When movies are over an hour and a half,

3:24

I struggle to continue whether the film

3:26

is really interesting or not. I just get

3:28

bored easily and have to watch them in

3:30

two parts or even three. And I even

3:32

avoid watching films if I see they are

3:35

too long. Right. We have more evidence

3:37

that this is a problem. We've been

3:39

getting reports that the major streaming

3:41

services have started changing the way

3:43

that they make original movies to better

3:46

match their audience's reduced ability

3:49

to pay attention to them. Uh, in a

3:51

recent podcast interview, Matt Damon,

3:53

who has a new movie out with Ben Affleck

3:55

on Netflix that's called The RIP,

3:58

said that streamers are now pushing

4:00

filmmakers to avoid the classic

4:02

three-act structure and to instead, and

4:04

I'm quoting him here, reiterate the plot

4:07

three or four times in the dialogue

4:08

because people are on their phones while

4:10

they're watching. In another part of

4:12

this interview, Damon says, uh, another

4:14

change is the streamers now say you have

4:16

to have a major action setpiece in the

4:18

first five minutes, otherwise people

4:19

will get bored and flip away. This is

4:22

very different to the way that we used

4:23

to make movies where you save the big

4:25

action sequence for act three. People

4:27

aren't going to last that long anymore.

4:30

Uh, I'm I couldn't help when I was

4:32

thinking about that idea that you have

4:34

to have the major thing happen in the

4:35

first five minutes. I couldn't help

4:36

thinking about the making of the

4:38

Godfather. I'm reading another book that

4:40

talks about this recently and an

4:42

interesting tidbit about the making of

4:44

that movie is that uh nothing major

4:48

happens with Al Pacino's character of

4:50

Michael Corone Corleó

4:53

um until about an hour and 15 minutes

4:54

into the movie where he shoots Captain

4:56

McCcluskey. And so Pacino rightly

4:59

looking at the full duration of this

5:01

three-hour movie said, "I need to play

5:04

Corleó very sort of quiet and meek." And

5:08

then that's like a key character

5:10

transition point. Well, when Copelo

5:12

began filming this movies in the first

5:14

dailies were coming back, the head of

5:15

Paramount, Robert Evans, was like,

5:17

"Pacino's got to go." They're looking at

5:19

the sequences from the wedding the

5:21

wedding scene up front like this guy's

5:22

barely talking. Like he's barely moving.

5:24

Like this is the wrong person. We got to

5:26

fire them. So, so Copela had to actually

5:29

move up the filming of the restaurant

5:32

shooting scene way early into the

5:35

schedule just so they could show those

5:36

dailies to Robert Evans. At which point

5:38

he's like, "Oh, I see what's going to

5:39

happen later. No, no, Pacino's got to

5:41

stay." But it just caught my attention.

5:43

We used to be okay with an hour and 15

5:45

minutes going by before the main

5:48

character talks above like a quiet

5:50

whisper. Not the case anymore. All

5:52

right, enough movie geekdom. Let's get

5:54

back on track here.

5:56

The next follow-up question is why are

5:59

we having a hard time paying attention

6:01

to movies? Well, if we return to the

6:02

Atlantic article, there's a lot of

6:04

quotes in there that point towards

6:07

digital technology and a particularly

6:09

smartphones as being the culprit.

6:12

The first piece of evidence is the quote

6:14

from uh earlier in this episode. Notice

6:16

that that professor said this issue got

6:19

really bad after the pandemic. What

6:22

happened in the pandemic? young people

6:25

began to uh obsessively use their

6:28

devices because they were stuck at home

6:29

at a level they haven't seen before. So

6:31

there's a lot of device related issues.

6:32

They got really bad after the pandemic.

6:34

So that is a a big piece of correlative

6:37

evidence right there. There's also some

6:39

quotes from the article that make this

6:40

clear. I'm going to read you one. All

6:42

right, this is from the article. Mazuda

6:44

Lipit, a cinema and media studies

6:46

professor at the University of Southern

6:48

California, home to perhaps the top film

6:50

program in the country, said that his

6:53

students remind him of nicotine addicts

6:55

going through withdrawal during

6:58

screenings. The longer they go without

7:00

checking their phone, the more they

7:01

fidget, eventually

7:03

they give in. All right, here uh so why

7:06

is this going on? Here's another quote

7:08

from the article that I think helps like

7:10

unwind what's happening in these

7:12

students brains. Students arriving in

7:14

college today have no memory of a world

7:16

before the infinite scroll. As

7:18

teenagers, they spent nearly 5 hours a

7:20

day on social media, with much of that

7:22

time used for flicking from one short

7:23

form video to the next. An analysis of

7:25

people's attention while working on a

7:27

computer found that they now switch

7:28

between tabs or apps every 47 seconds

7:30

down from once every 2 and 1/2 minutes

7:32

in 2004. I can imagine if your body and

7:35

or your psychology are not trained for

7:36

the duration of a featurelength film, it

7:38

will just feel excruciatingly long.

7:40

USC's lip said. All right. So, I mean,

7:43

not a surprise, but these film

7:44

professors point their finger at the

7:46

obvious culprit. Phones

7:48

have made it hard for people to focus on

7:50

movies.

7:52

Now, I want to get a little bit more

7:53

technical here. There's actually a term

7:56

of art for the capability

8:00

that phones are degrading. The term is

8:04

cognitive patience. Now, this was coined

8:07

by the reading re researcher Maryanne

8:10

Wolf. Uh here's the formal definition of

8:13

this term which is reading specific but

8:15

we're going to generalize it to to

8:16

movies as well. Here's the formal

8:18

definition of cognitive patience. The

8:20

ability to read with focused and

8:22

sustained attention and delay

8:23

gratification while refraining from

8:25

multitasking or skimming over parts of

8:27

the text. So we can adapt this idea of

8:29

cognitive patience. I can sustain

8:31

attention on something for a long period

8:33

of time without switching context or

8:35

multitasking. We can really apply that

8:36

to multiple other activities including

8:39

consuming films. Our

8:42

cognitive patient seems to have been

8:44

degraded

8:46

by using our phones. All right. Well, if

8:49

we're going to solve this problem, let's

8:50

try to understand again in more detail.

8:54

Why is cognitive patients degraded by

8:57

looking at our phones all the time?

9:00

There's two things going on here that

9:01

have to do with the reward systems in

9:03

our brain. The first has to do with our

9:05

short-term reward system. So, there is a

9:08

bundle of neurons in your short-term

9:11

reward system that is associated with

9:14

the stimuli of picking up and looking at

9:16

your phone. And because you get this

9:18

consistent strong source of reward that

9:21

has high expected value when you pick up

9:23

your phone because of the algorithmic

9:24

curation of the apps that are on there,

9:27

those bundles have learned we will

9:30

probably get a good reward if we do

9:31

that. So what happens, and I'm

9:32

simplifying things here, is that bundle

9:34

of neurons effectively votes for picking

9:37

up your phone as your next action. If it

9:40

sees it nearby, you experience that vote

9:43

subjectively

9:45

as an urge to pick up that phone, a

9:47

distracting urge to pick up that phone.

9:49

There's a dopamine cascade that happens

9:51

through your neuronal, you know, motor

9:53

neurons. There's a whole thing here.

9:54

We're going to get into this more. By

9:55

the way, I'm having Anna Lympa is going

9:57

to come on the show to teach us more

9:59

about dopamine, but it feels like an

10:01

urge to pick up the phone. So, if you

10:04

have a phone with you and you're trying

10:07

to watch a movie,

10:09

there's all of these votes happening.

10:11

Those neurons are like reward, reward,

10:13

reward, let's go, let's go, let's go.

10:15

And you are feeling this like jittery,

10:17

as that one professor said, nicotine

10:19

addict style withdrawal symptoms because

10:21

your brain is like this is here, this is

10:24

reward. It's the same thing like if

10:25

you're hungry and there's the you have

10:27

the the big bowl of popcorn in the

10:30

movies, right? I don't know if you have

10:32

this problem, Jesse, but I often tell

10:33

myself not till the previews are over.

10:36

It's really hard because there's a

10:38

bundle of neurons. It's like that's

10:39

going to be good when we eat that

10:40

popcorn. Boom, boom, boom, vote, vote,

10:42

vote. And you're like sort of sitting

10:43

there shaking. Uh because it's right

10:45

there and it's hard to overcome your

10:46

short-term reward system. So our

10:48

constant use of the phones builds up a

10:50

very strong vote from that neurona

10:52

bundle which makes it difficult to do

10:53

anything else when the phone is there.

10:56

But the second thing that happens is

10:58

that because of that we lose our

11:00

exposure to the deep delayed

11:03

gratification rewards of actually making

11:06

it through a good movie. Now why is that

11:08

important? Well, there's a different

11:10

reward system in our brain. a long-term

11:12

reward system that can override the

11:15

short-term reward system and it deals

11:18

with not immediate guesses of if we do

11:20

this thing, what's the reward? It

11:22

predicts the future. If we do this thing

11:25

now, it actually might not in the moment

11:27

be the best feeling thing, but in the

11:29

future that's going to give us a good

11:31

reward. Um, not a cheap reward like the

11:34

the sad that comes from eating popcorn,

11:35

but like maybe a deep psychological or

11:38

philosophical type of reward. That

11:40

long-term reward system could overwhelm

11:42

the short term, but it has to be

11:45

trained. And the way you train that

11:46

long-term reward system is that time and

11:48

again, you delay gratification. You get

11:50

the deep reward in the end, the deep

11:51

satisfactions. It strengthens its case

11:53

in the future for like it's worth

11:55

sticking with this activity.

11:57

So, we have this anti virtuous cycle

12:00

where the the phone makes it harder and

12:02

harder to watch things when it's there.

12:04

So, you get less exposure actually

12:06

making it through good movies. So, your

12:08

long-term reward system loses its

12:10

standing. And now, when you're in a

12:12

situation where even your phone's not

12:13

there, you're just like, I don't I'm

12:15

bored. Like, I don't want to make it

12:16

through here because there's no

12:17

motivation left for you to actually make

12:19

it through the film. So, those two

12:20

things work together and in the end, you

12:22

can't watch the film. Now, should we

12:23

care about it? What if you don't like

12:24

movies? Well, I say yes because it's a

12:27

canary in the coal mine. Movies are just

12:30

one example from a broader c category of

12:32

activities that uh are moving and

12:34

meaningful and can change the way we

12:35

understand the world and ourselves

12:39

and we're getting pushed away from that

12:40

because of what's happening on these

12:42

devices.

12:44

So whether or not you like movies,

12:46

there's some equivalent of that in your

12:48

life

12:50

that you are probably being pushed away

12:52

from because of the dominance of your

12:54

short-term reward system and how that

12:56

leads to the long-term reward system

12:57

with these other activities to degrade.

13:00

So this is like a bigger trend that's

13:02

being picked up by this specific issue,

13:04

this bigger trend that

13:06

activities that give us deep

13:08

satisfactions almost always require

13:10

delayed gratifications and and cognitive

13:12

patience, right? And the more time we

13:14

spend on our phones, the worse we get at

13:17

actually sticking with those activities.

13:19

How many things like watching movies are

13:21

leaving our lives that we don't even

13:22

know. So I think it is something worth

13:26

dealing with. Like the first step

13:27

towards reclaiming our brain is

13:29

beginning to rebuild cognitive patience

13:32

especially around activities that can

13:33

give us deeper satisfactions. And I

13:36

think movie watching is a great first

13:39

tool that we can use. So here's my

13:40

physical analogy, right? I mean, I think

13:42

about the ability to make it through a

13:44

good movie. We should think about that

13:46

like if you're new to running, your

13:48

ability to actually like complete a 5K

13:50

race. It's like that first milestone you

13:52

want to get to that says, "I am now

13:54

starting to reclaim my brain. I am now

13:56

starting to actually build up some

13:58

cognitive fitness." It's not where you

13:59

end, but it should be your first step.

14:02

So, this is my pitch to you today. Let's

14:04

let's make this our exercise. Relearning

14:07

how to build up the cognitive patience

14:09

to make it through a good movie. And

14:11

we're doing this not just because movies

14:13

are cool, which they are, but because

14:14

again, we want what I call attentional

14:16

autonomy, the ability to actually have

14:18

more control over what we do with our

14:19

brain and not just what's going to give

14:21

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know we sent you. All right, Jesse,

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let's get back to the show. All right,

17:32

so this brings us to the practical

17:33

segment of this discussion.

17:36

How do you teach yourself

17:38

to make it through and enjoy

17:41

good movies?

17:44

Well, I have two general categories of

17:47

things to suggest. Okay. Um, the first

17:49

category of things to suggest is when

17:51

you sit down to try to watch these

17:52

movies, you have to get the stimuli

17:54

that's that is going to trigger the

17:56

short-term reward system out of the

17:57

room. Do not have your phone with you.

18:00

But you're just setting yourself up for

18:01

failure. here, the nicotine addict,

18:03

shaky withdrawal if the phone is right

18:04

there because it's going to fire those

18:06

votes again and again and again. And why

18:08

combat that? Why combat that? Put the

18:11

phone far enough away that it's not

18:13

triggering your short-term reward

18:15

center. All right? So, that's going to

18:16

help. And if you're in a movie theater,

18:19

for God's sakes, I hate seeing this,

18:21

Jesse. I don't know if you see this now,

18:22

but because of that reward signal,

18:24

people are looking at their phones. They

18:25

can't help themselves. So, it's almost

18:27

easier to practice this at home because

18:30

you can put your phone very far away in

18:31

the movie theater. People are just like,

18:32

you know what? I'm just going to look at

18:34

it because, you know, I don't know, they

18:36

can't help themselves. All right. Number

18:38

two, so that gets that helps the

18:41

short-term reward system to greatest

18:42

influence. Number two, we have to uh

18:45

rebuild your association of long-term

18:48

reward. So, keep the movies good. That

18:51

is movies with enough sort of art or

18:53

artifice that you're going to end them

18:54

with a deep satisfaction. I was exposed

18:56

to something new. It was a moving

18:58

experience. It was an inspiring

18:59

experience. The the craft was really

19:01

inspiring. The the story was really

19:03

inspiring because again, the more

19:05

exposure you get to a moving experience

19:07

at the end of a movie, the more standing

19:09

you're giving to your long-term reward

19:11

system and the easier it will be to do

19:12

this in the future. So, how do you now

19:15

make it all the way through a good movie

19:17

if you're not used to watching movies

19:18

that aren't uh every six minutes there's

19:21

some sort of alien that's attacking? How

19:22

do you make it through these movies?

19:24

Here is my technique that I use. I'm

19:26

going to give it to you now for the

19:27

first time. Never talked about it

19:28

before. I call it the 30-minute rule.

19:31

You never go more than 30 minutes

19:34

without stopping to read something about

19:36

the movie. Right? So before you start,

19:38

you read a review or analysis of the

19:40

movie. And if it's a good movie, there's

19:41

going to be a lot written about it. So,

19:43

oh, I kind of understand. Why do people

19:45

like this? What should I be looking for?

19:46

Great. You watch 30 minutes. Stop. Give

19:49

your brain a little bit of a break. Read

19:51

another reviewer analysis. Start it up

19:54

again. go another 30 minutes, stop, read

19:55

another review or analysis. You're

19:57

always repringing your brain

20:00

with ideas about why this movie is good,

20:03

what you should be looking out for, why

20:05

people liked it, and just increases its

20:07

attractiveness or salience to your brain

20:09

and makes it easier to pay attention and

20:12

it amplifies the reward you get out of

20:14

it. I am not a big fan of this movement

20:16

of like exposure to art. Just go to the

20:20

museum and then you'll learn to love

20:21

art. It doesn't work that way. You got

20:23

to know what you're looking at and why.

20:25

Or just say, "Watch this movie. It's

20:28

great." Like, it can work. Some great

20:29

movies will will get the people, but a

20:31

lot of classics people like, "I'm

20:32

bored." Right? So, you need to know what

20:35

makes it great and it amplifies the

20:38

reward you get from the experience with

20:39

gives your long-term reward system more

20:41

standing. And now you can your cognitive

20:43

patience expands. Now, here's my extra

20:46

secret tip. This is this is one I like

20:48

because I like both the art of movies,

20:49

but also the craft of movies. If I'm

20:51

watching a classic, I always search to

20:54

see if there's an article written about

20:56

it for American cinematography magazine,

21:00

uh, magazine for cinematographers,

21:02

right? A lot of movies will have these

21:05

articles where the cinematographer, I

21:06

guess now they often call these director

21:08

of photographies as well, um, write a

21:11

long essay about how they shot the

21:14

movie, what they were thinking about,

21:16

the techniques they introduced, and why

21:18

they introduced them. you learn about uh

21:20

different lighting choices they make and

21:22

different lensing choices they make. I

21:24

always come away from those articles

21:26

with this like I I see the movie through

21:28

a different light. I'm like, "Oh my god,

21:29

look what they did in this scene. This

21:30

is great." All this amplifies reward.

21:33

All right, so that's what I'm going to

21:34

recommend.

21:36

What should you watch

21:38

this? Okay, you know this, Jesse. I

21:40

can't do top 10 list. I'm like I There's

21:43

a word for this. Like I I can't rank

21:45

things. I can't see what my favorite

21:47

things are. So, I can't tell you like

21:48

these are the 20 best movies or the 10

21:50

best movies or whatever. Um, but I just

21:52

went through and I listed I was thinking

21:53

through like if I was someone was like

21:55

wanting to get into watching good

21:56

movies, what are some movies I would

21:58

recommend? And I just threw a bunch down

21:59

that these are all movies that are

22:01

meaningful to me and I think they have

22:03

like really clear sources of value if

22:07

you do my 30 minute rule and read about

22:09

them or why they're uh important. So, I

22:11

have these in rough chronological order

22:14

here. Um, on the older side, consider

22:17

watching M, the German Fritz Lang movie

22:20

about actually uh, it's not a very

22:22

cheery topic, Jesse. It's about a I

22:25

guess like a child's abducting serial

22:27

killer, but it's from the 30s. Um,

22:32

so atmospheric. It's kind of touches on

22:35

German expressionism. So many like

22:36

innovations in it. It's actually a

22:38

really good movie. Watch Citizen Kane.

22:40

Citizen Kane kind of fell out of uh, I'm

22:42

obsessed with this movie. kind of fell

22:44

out of favor because what happened is a

22:46

lot of people watched they were like

22:47

what's so great about this? What you

22:49

have to do to understand that is watch

22:50

another movie made that same year.

22:52

You're like oh this is great because he

22:55

invented Wells invented like all of

22:57

these techniques that now we're used to

22:59

from from sophisticated movies. They

23:01

weren't in the movies before it. I mean

23:03

he has nonline nonlinear narratives. He

23:05

has uh the sort of um the the types of

23:09

cuts, these type of tracking shots, his

23:11

use of long focus. his even like little

23:13

things like I'm going to build a ceiling

23:15

on this set because I want to be able to

23:16

shoot low and they actually had a the

23:19

floor of the set up on a platform so a

23:21

cameraman could be down in a pit and but

23:23

to shoot up you have to have a ceiling

23:25

and so they built a fake ceiling on the

23:26

set. Uh he just innovated the the the

23:29

cinematography in this the the the

23:30

darkness, the shadows like this 20

23:33

whatever something like 27 or something

23:35

comes in from radio and just innovates

23:38

innovates innovates innovates the most

23:39

innovations in a single movie technical

23:41

innovation since probably Birth of a

23:42

Nation but with 100% less Clueless Clan

23:46

members. So like that's good. Um so I'm

23:48

a big Sis Kane fan. If you can watch it

23:50

with the audio commentary that's worth

23:52

it. You got to watch John Ford. You got

23:54

to watch the Searchers. You got to watch

23:56

Vertigo uh by Hitchcock. You gotta watch

24:00

um uh The Good, the Bad, and The Ugly. I

24:04

think that's that's my favorite Clint

24:05

Eastwood from that period. You got to

24:07

watch Bonnie and Clyde. Read about

24:09

Bonnie and Clyde before you watch it.

24:12

This introduced new Hollywood. Read

24:14

Pauline Kale on it. Read uh Eert on it.

24:17

There's I think Bonnie and Clyde.

24:18

There's a famous review. I don't know if

24:19

it's Morgan Stern, who it is, who didn't

24:21

understand it because Bonnie and Clyde,

24:23

you know, this is Warren Batty,

24:24

Hackman's in it. Uh, it was bringing

24:28

like a European style personal film

24:30

making to Hollywood just as the studio

24:32

system was collapsing, right? Like this

24:34

was we went from The Sound of Music to

24:36

Bonnie and Clyde. It's it's a European

24:38

style film in the sense it's more

24:40

personal. It's more nihilistic. It's

24:42

it's it's playing on like emotional

24:43

realism or whatever. And there's a

24:45

famous review of it that's like this is

24:47

garbage. And then they had to go back

24:48

and write a new review like I was wrong

24:51

actually. This is a classic. So you got

24:52

to watch that. You got to watch Jaws

24:55

arguably like the platonically perfect

24:57

movie of the 20th century. Um then you

25:00

got to watch some of the new Hollywood7s

25:02

some other naturalist movie naturalism

25:04

rich movies. I would suggest uh Dog Day

25:06

Afternoon is good. Um the city ltt

25:10

Nashville I think is very good. You

25:12

listen to the Robert Altman working with

25:14

these multi-track recorders that have

25:16

overlapping naturalistic dialogue. I

25:18

also like McCabe and Mrs. Miller.

25:19

Speaking of Batty, which is like another

25:21

Altman movie of that era. It's like a a

25:25

realist naturalist reinterpretation of a

25:27

western. Watch that after The Searchers.

25:30

That's a cool double feature you're

25:31

going to get right there. Um Taxi

25:34

Driver. I mean, it's an unsettling

25:35

movie, but man, the camera work in

25:37

there, the confidence of that movie. Uh

25:40

let's go modern like 21st century.

25:42

Dunkirk I think is uh a masterpiece of

25:45

writing and film making. Um I think I've

25:48

been pushing Zone of Interest. Not a

25:51

very cheery movie. Takes place right

25:53

outside the gates of Ashwitz. So I guess

25:55

you could double feature this with Fritz

25:56

Lang movie. Um I think it's a

25:58

masterpiece. There's there's a lot about

26:00

that movie. It's so original the way

26:01

that it was like crafted and

26:02

constructed. I saw in the theater. I

26:04

think it's fantastic. Um, if you want

26:05

something that's in the theaters now,

26:07

the best thing I've seen recently is

26:08

Marty Supreme. It's one of the Softy

26:10

Brothers. Uh, fantastic kind of, again,

26:13

you got to read about it, right? It's

26:14

it's commentary on the American

26:17

experience, on capitalism, on the

26:19

tension between ambition and family and

26:21

where we come from and is beautifully

26:23

shot and acted and the energy. It's just

26:24

like a really well done thing. All

26:26

right, so I don't know. I'm leaving out

26:28

all good movies, but that's a place to

26:30

get started. What am I missing, Jesse? I

26:33

mean, crossroads should be most of your

26:36

time.

26:37

>> I saw that in the theater. I saw that in

26:40

the theater and got yelled at by the

26:42

people behind me.

26:43

>> What happened?

26:44

>> I was making fun of it so much that at

26:46

the end of the movie they were like,

26:48

"You ruined this for us because you

26:49

wouldn't shut up." And I like it was so

26:51

bad.

26:52

>> Like, you should have been on your phone

26:53

so you were distracted by me.

26:54

>> Yeah, that's the problem. Nowadays, they

26:56

wouldn't have noticed. They would have

26:56

been on their phones. Oh, man. What am I

26:58

missing?

26:59

>> Well, Robert Dval just passed away.

27:01

>> Yeah. Okay, we we got to do some like

27:03

Devol

27:05

on him.

27:06

>> Yeah, you got to watch Apocalypse Now.

27:07

There's there's such great beautiful

27:09

remasterings of that of that movie. It's

27:11

visually beautiful. That's a fantastic

27:13

movie. Colonel Kilgore. That's classic.

27:15

Duval Godfather

27:18

one and two. It's like out of favor to

27:19

say that's good. It's a great movie and

27:21

he's great in that.

27:22

>> He wasn't in three because they weren't

27:24

going to pay him enough.

27:25

>> Yeah. And three wasn't very good.

27:26

>> Yeah. Three was horrible.

27:27

>> Um The Great Santini. He's very good. I

27:30

think Robert Deval's I mean his

27:33

>> he was in network too.

27:34

>> He was in network is a great movie. Um

27:36

his most challenging role and I

27:38

hopefully the role that he's remembered

27:39

for and the one that you should watch I

27:41

think is his appearance as the father of

27:45

the um Vince Vaughn character in Four

27:49

Christmases.

27:51

That's an underrated movie. My wife and

27:53

I love the the it's like a 2006 movie

27:56

Four Christmases. It's Reese Witherspoon

27:58

and Vince Vaughn at the end of that era

28:00

where like you would just put Vince

28:01

Vaughn in a movie and he would talk fast

28:04

and it was kind of funny and Robert

28:05

Duval played his like functional

28:07

alcoholic divorced father.

28:09

>> Mad Dog had a critic on talking all

28:11

about him and he said that he was

28:13

offered the Jaws leading role but he

28:14

didn't want to be a main guy.

28:16

>> Yeah, I know a lot about I just read

28:18

reading about again everyone was offered

28:20

those roles and you know how Schneider

28:21

got it. Spielberg was like at a thing

28:25

socially with Schneider and was uh just

28:29

telling about the movie and he's like

28:31

why don't you put me in the lead and

28:32

he's like you know what yeah that makes

28:35

sense and that was that and that's how

28:36

he ended up in the and they they put him

28:38

in the lead Schneider. All right we're

28:40

going to take another quick break to

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All right, let's get back to the show.

31:10

Um, all right. So, that's what we got.

31:12

Watch more movies. All right, we're

31:15

going to move on now with our news and

31:18

notes.

31:21

All right. So, I got to react to

31:23

something that uh I've been sent a lot

31:25

of times. I think a lot of people have

31:27

been sent this a lot of times. It's an

31:28

essay that's been going around on X that

31:30

went viral. It's written by an AI

31:32

startup entrepreneur named Matt Schumer.

31:34

And the essay is called something big is

31:38

happening. And it is a uh right down the

31:41

middle AI is about to change everything

31:44

for real this time. Let's all be worried

31:45

type of essay. I got sent this so many

31:47

times. For whatever reason, this crossed

31:49

over in the normie culture and out of

31:51

tech culture and tech journalism

31:52

culture. Everyone seems to be reading

31:53

this. So, by popular demand, I'm going

31:56

to go through this a little bit. Uh I

31:58

I've picked out three or four uh

32:01

sections I think are important for

32:03

understanding the message and approach

32:05

of this essay and then I'm going to

32:06

respond to it and we'll try to get down

32:09

to the ground truth here. So, I'll have

32:10

this on the screen here for people who

32:12

are watching instead of just listening.

32:14

All right. I'm going to read something

32:16

here. I'll start with something from the

32:18

introduction to the piece. All right, so

32:19

here's Matt Schuber. I've spent six

32:21

years building an AI startup and

32:23

investing in the space. I live in this

32:25

world and I'm writing this for the

32:26

people in my life who don't. My family,

32:28

my friends, the people I care about who

32:30

keep asking me, "So, what's the deal

32:32

with AI?" and getting an answer that

32:34

doesn't do justice to what's actually

32:35

happening. I keep giving them the polite

32:37

version, the cocktail party version,

32:39

because the honest version sounds like

32:41

I've lost my mind. And for a while, I

32:42

told myself that this was a good enough

32:44

reason to keep what's truly happening to

32:46

myself. But the gap between what I've

32:48

been saying and what is actually

32:49

happening has gotten far too big. The

32:52

people I care about deserve to hear what

32:53

is coming, even if it sounds crazy. All

32:57

right, that's quite the setup there. Um,

32:59

there's some sort of classic AI

33:01

reporting traps that are happening here.

33:02

There's no actual information in it.

33:04

It's pure emotional manipulation trying

33:06

to give you a sense of the digital ick,

33:08

make you feel uneasy. It sets you up for

33:10

this. what the emotional state it puts

33:12

you in if you're not someone who's

33:14

following AI closely is like, "Yeah,

33:16

your your worst suspicions are true.

33:18

It's crazy what's going on out there."

33:20

And you know what? All right, I'm going

33:22

to let you in. What's going on? That is

33:24

a classic before we get to the content

33:26

of this essay. That is a classic move.

33:28

Like, I'm going to reveal to you what's

33:30

happening and it's worse than you think.

33:31

I mean, that's like the classic move for

33:33

everything. Um, conspiratorial thinking,

33:36

for radical health trends. It's a very

33:39

compelling way to set up whatever you're

33:40

going to say. All right, let's get into

33:42

the content itself. I'm going to skip

33:43

ahead a little bit now. Here's the

33:46

first, I think, substantive thing that

33:47

said here. For years, AI had been

33:50

improving steadily. Big jumps here and

33:52

there, but each big jump was spaced out

33:54

enough that you could absorb them as

33:56

they came. Then, in 2025, new techniques

33:59

for building these models unlocked a

34:01

much faster pace of progress. And then,

34:03

it got even faster and then faster

34:04

again. Each new model wasn't just better

34:07

than the last, it was better by a wider

34:09

margin, and the time between new model

34:11

releases was shorter. I was using AI

34:13

more and more, going back and forth with

34:15

it less and less, watching it handle

34:16

things I used to think required my

34:19

expertise. All right, I'm going to stop

34:20

right there. This is our first piece of

34:23

evidence that, oh, this writer is

34:25

willing to essentially make things up if

34:29

they fit the vibe that he's trying to

34:31

portray.

34:32

The way he describes this is actually in

34:35

some sense the opposite of reality. As

34:38

someone who has been covering the AI uh

34:41

this the generative AI revolution very

34:43

closely for the New Yorker and here for

34:44

this show, this is not how things

34:47

happen. It's opposite.

34:50

Things were moving really fast when

34:52

pre-training scaling was working. The

34:54

jump from two to three and three to four

34:57

were these impressive leaps. This is

34:58

where you're in the steep part of the

35:00

the lost power law curve from the Kaplan

35:02

scaling paper. The period he's talking

35:04

about as we arrived into 2025 is

35:07

actually when progress slowed down.

35:10

It became a problem for the AI

35:12

companies. the general overall

35:14

capability boost that happened from

35:16

pre-training scaling stopped happening

35:19

and they had the shift instead to a

35:21

backup plan which was we're going to do

35:24

this sort of post-training work on very

35:26

specific tasks and we're going to do

35:28

things like post inference time compute

35:30

and we're going to turn our focus from

35:31

like general ability improvements that

35:33

are clearly impressive to any user to

35:36

instead chasing down these arcane named

35:38

benchmarks that we can sort of teach the

35:40

model to specifically do well on and

35:42

there was this whole period where this

35:44

was a real for users were like I don't

35:46

really the main thing I'm noticing is

35:47

like the personality of the chat bots

35:49

changing and you were getting

35:50

incremental improvements on specific

35:52

activities where they could specifically

35:54

try to post train for that activity it

35:56

was actually a bad period for growth not

35:59

a good period so this idea that changes

36:01

were speeding up um most I would say

36:04

close watchers are saying no no this

36:07

actually slowed down and they had to try

36:10

to find specific areas where some sort

36:12

of notable improvement could make. They

36:13

found video generation was one that that

36:15

ended up being a bit of a bust. And then

36:17

the other place was uh in computer

36:19

programming tools. So I think he's

36:21

extrapolating

36:22

uh continued progress on the computer

36:25

programming tools which I'll get into in

36:26

a second was not exponential but hard

36:28

one with like the models in general were

36:31

getting faster at some sort of bigger

36:32

pace. It's simply not true. I know it

36:34

fits the vibe of people talking about

36:36

cloud code more but it's simply not

36:39

true.

36:41

All right, so let's uh read the rest of

36:43

this quote here. Then on February 5th,

36:45

two major AI labs released new models on

36:47

the same day. GPT53 codecs from Open AAI

36:50

and Opus 4.6 from Anthropic. And

36:53

something clicked, not like a light

36:54

switch, more like the moment you realize

36:56

the water has been rising around you and

36:57

is now at your chest. Again, these were

37:00

just continued incremental improvements

37:02

on these coding related agents, which

37:04

I've been reporting on for a while. Um,

37:07

they've been impressive for a while. the

37:09

they've been making progress in these

37:11

somewhat frequent but relatively small

37:13

steps that are built on fine-tuning and

37:15

other types of post-training that

37:16

they're doing specifically around

37:18

programming tasks. There is something

37:20

like an inflection point where the the

37:23

latest model these latest models on

37:25

certain sorts of like code

37:27

autogeneration agentic autogeneration

37:29

task like it got just to a level where

37:31

more and more people were like I think I

37:32

can start using this more in my

37:34

day-to-day. So, but these are kind of

37:35

technical shifts

37:37

and they're very focused on what's

37:39

specifically happening in programming.

37:40

So, the idea that there's this these

37:42

models in general are exponentially

37:43

speeding up. This is the opposite of

37:45

exponential incremental steady progress

37:47

on a small number of narrow applications

37:49

where other applications that they

37:50

thought the models would be much better

37:52

at. So far, they failed to be making

37:54

progress on. All right, let's jump into

37:55

the details of the programming itself.

37:58

Matt writes, I am no longer needed for

38:00

the actual technical work of my job. I

38:02

describe what I want built in plain

38:04

English and it just appears. Not a rough

38:05

draft I need to fix to finish thing. I

38:07

tell the AI what I want. Walk away from

38:09

my computer for four hours and come back

38:11

to find the work done well. Done better

38:15

than I would have done it myself with no

38:16

corrections needed. A couple of months

38:18

ago I was going back and forth with the

38:19

AI guiding it making edits. Now I just

38:21

describe the outcome and leave. I'll

38:24

skip the final details here. Um, so he's

38:26

saying in the narrow world of computer

38:28

programming, this is the inflection

38:30

point advance that you can now as a

38:32

computer programmer just tell the AI

38:34

this is what I want and come back four

38:35

hours and you have that app built. He

38:37

goes on to talk about that it not only

38:39

builds the app, it tests the app, it

38:40

fixes it. You don't have to do anything

38:42

anymore. All right. Um, so is this how

38:46

people are now using this technology,

38:49

the latest models that were released

38:50

earlier this month? Uh, well, who can

38:53

tell? I can tell because I'm in the

38:56

middle of a reporting uh project that I

38:59

started just last week. So with the

39:01

exact models he's talking about where I

39:03

have so far rel received detailed notes

39:06

on how they use AI from active computer

39:10

programmers. I have over 250 such case

39:12

studies. I've made my way through about

39:13

half of them so far. So I'm still kind

39:15

of early in this progress. But here's

39:16

what I can tell you.

39:19

No one is saying make me an app and

39:21

walking away and coming back four hours

39:23

later and is like there I have it let's

39:24

release this. That is not how

39:26

programmers are using these very latest

39:28

tools. That only works for very specific

39:31

types of apps. They have to be in one of

39:34

a small number of like very common style

39:36

of applications that are much more and

39:38

it's like a special languages sort of

39:40

interface um focused not too big and you

39:43

don't need to be particularly stable. So

39:45

you can as like a hobbyist

39:48

kind of vibe code, hey, can you make me

39:49

a Tetris game with, you know, uh,

39:51

Dungeons and Dragons characters or

39:52

something and it will like do that. You

39:54

can come back, you'll have something.

39:56

But the 250 serious programmers I'm

39:58

talking to, that's not the way they're

39:59

using the auto code generation. U, um,

40:01

it's much more narrow and specified.

40:04

Those who are doing this, and a lot of

40:05

them aren't, those who are doing this

40:07

talk a lot about how there's these super

40:10

clear specs. This is exactly what I want

40:12

you to do. And then they let the they

40:14

they let the model build that code uh

40:17

for this piece and then they have to

40:19

extensively test it because again the

40:20

models make mistakes 20% of the time,

40:22

right? Um and then they run a bunch of

40:24

unit testing on it. Okay, I think this

40:25

is working. Let's integrate that in.

40:28

Okay, now here's the next thing I need

40:29

you to do. And like one out of five of

40:31

these attempts are like, okay, the AI

40:32

just doesn't get it. I'll just do it

40:33

myself. There's a lot of interesting

40:36

stuff happening here with AI. But what

40:37

he's describing so confidently is what

40:39

I'm a minuscule fraction of this broad

40:42

sample of real active professional

40:43

computer programmers I talked to a

40:45

minuscule fraction is using the tools in

40:48

this way. It's cool what's happening but

40:51

it's not hey go make me go do this I'll

40:55

come back four hours later it's just

40:56

done and I'm moving on in my life there

40:58

these are heavily supervised right now.

41:00

All right u let's keep rolling here. Uh

41:03

here's the next quote from the piece I

41:05

want to highlight. The AI labs made a

41:07

deliberate choice. They focused on

41:09

making AI great at writing code first

41:11

because building AI requires a lot of

41:13

code. If AI can write that code, it can

41:15

help build the next version of itself. A

41:17

smarter version which writes better code

41:19

which builds an even smarter version.

41:21

Making AI great at coding with a

41:23

strategy that unlocks everything else.

41:25

This is gradea nonsense.

41:29

It's just vibing nonsense.

41:32

These AI agents do not let us make

41:36

better AI models. That's not how that

41:39

works. That's not what's happening

41:42

there. They they're very useful

41:45

especially like if you talk to these

41:46

programmers like I've been doing. The

41:49

reason why they're saving time is that

41:51

it's there's a lot of very tedious tasks

41:54

that happen when you build various

41:55

software stacks or applications like

41:58

building out the interface and

41:59

connecting all the interface elements to

42:02

you know like the right functions or

42:03

integrating multiple different data

42:05

sources into you know a common framework

42:08

so that you can pull data from any of

42:10

them. Um this is tedious type of coding

42:13

especially if you're not an expert at

42:14

exact like you haven't built a hundred

42:15

of those type of apps before and it

42:17

takes people a long time because they

42:18

have to look up oh god what's the

42:20

library call for the button what's the

42:23

what do I how do I access this sort of

42:25

data source here for this what's the

42:27

call I got what do I have to import and

42:29

uh this type of stuff these models can

42:31

do automatically they know it already

42:33

like god that saves me so much time it's

42:34

so tedious I don't have to do the

42:36

tedious thing what they cannot do is

42:38

like invent a new

42:42

model of intelligence, improve the

42:44

fundamental mathematics of like machine

42:47

learning, you know, build us a a better

42:50

model for AI than we've ever seen

42:52

before. That's not how this works. None

42:55

of the innovations in generative AI are

42:57

programming related innovations. They're

42:58

all conceptual mathematical innovations

43:00

where someone who is an expert in

43:02

machine learning realizes like oh

43:04

reinforcement learning could be applied

43:06

to a language model if we work through

43:08

the different reormalizations of the

43:10

vectors properly and then someone goes

43:11

off and programs it. So this idea that

43:14

uh tedious code or code that requires

43:16

you to look up a lot of information can

43:17

be automatically coded and that saves

43:19

you a lot of time. You cannot jump from

43:21

there to say oh AI can write itself now

43:23

and now we're going to have this

43:24

self-reinforcing loop. That idea has

43:26

been in the zeitgeist all the way back

43:28

to the 1960s when JL Good wrote the

43:31

first paper on ultra intelligence and

43:33

introduced the idea of recursive

43:35

self-improvement. Uh it is not not not

43:39

what these tools are meant to do. They

43:41

cannot do that. That's not what going

43:43

it's not what's going on. This notion

43:45

that the AI companies chose to build AI

43:49

agents fir I mean coding agents first so

43:52

that they could build better models that

43:54

could then do everything else is wrong.

43:57

The reason why we're hearing more about

43:58

coding agents is because it's one of the

44:00

only narrow tranches of applications

44:04

where they could find a market. They

44:06

didn't choose there's a lot of other

44:08

things the AI companies promised

44:10

products in. I just I wrote an article

44:12

back in January for the New Yorker about

44:13

this where in early 2025 they said this

44:17

is the year that we're going to have

44:18

these general use agents for all sorts

44:19

of jobs. We're there. It's going to

44:20

happen. It didn't happen because it

44:23

turns out that's much harder than coding

44:25

agents. They put a lot of effort in the

44:27

video generation and like that did

44:28

pretty well, but there was no market

44:30

there because people didn't want to pay

44:31

$200 a month to make Tik Tok videos.

44:34

They want there to be other markets.

44:37

They're just the technology is not good

44:38

enough. It's not interesting enough.

44:40

It's not helpful enough. We're not

44:41

seeing it move the needle in other

44:42

positions as much. So, we're hearing

44:45

about coding because it's like the only

44:46

place right now where there's real

44:47

progress being made and it is a good

44:50

market and this technology could be

44:52

really useful for programmers. Again,

44:53

I'm I'm doing these surveys and I'm

44:55

going to do a much bigger thing about

44:56

this soon.

44:57

But this is like a narrow thing that's

45:00

happening right now.

45:02

one of the places where these models

45:04

have always been good all the way back

45:05

to the the instruct model the instruct

45:07

GPT model that was helped to make the

45:09

GPD35 that chat GPT was made on from the

45:11

very beginning the last half decade

45:14

we've known the one thing these models

45:15

are good at is structured code because

45:17

it's very structured language with lots

45:18

of good training examples and they've

45:20

been making steady improvements on it

45:22

using post- training techniques and

45:23

they've been passing various milestones

45:25

as they do these and this is a good

45:26

story for the computer industry and it's

45:28

an interesting story we might lose jobs

45:30

we might gain jobs and we don't know and

45:31

we should cover Well, but the idea that

45:34

the AI companies chose to do that first

45:36

so that they could then make their own

45:38

models smarter and then there's going to

45:39

be this takeoff and AI takeover straight

45:43

up vibe nonsense. That's not what's

45:47

actually happening.

45:49

So, okay, I'm I'm going to leave it

45:50

here, Jesse, because this this this

45:51

essay makes me a little bit upset, but

45:54

let me be clear.

45:57

summarize

45:59

their struggles with the AI industry

46:02

post GPT4, the failure of project Orion,

46:04

the failure of the BMTH model, the

46:06

failure of uh the Gro 3 failure where

46:09

they moved to 100,000, you know, GPUs

46:11

for training and didn't get big

46:12

improvements, the shift towards post-

46:14

training, more incremental improvements

46:15

and benchmark chasing. I've written

46:17

about this. Look at my article last

46:18

August uh for the New Yorker for more

46:21

about this. This is the the portrait of

46:23

a an industry that's not like it's

46:25

failing, but it's also not going gang

46:27

busters. This is why, you know, the

46:29

right now the investment community is

46:31

like a little bit nervous about the

46:33

stocks for the big AI companies like we

46:34

we need to see where your big revenue is

46:36

going to come from and we're not seeing

46:37

it yet. It's like just a mixed story.

46:39

It's a cool technology. They're trying

46:41

to find markets.

46:43

They're finding some niche markets.

46:44

Customer service, uh, you know, video

46:46

production, that's a pretty small

46:48

market, but there's good stuff there.

46:49

And in programming, they're pretty good

46:50

at programming. and they've been making

46:52

steady incremental progress and the

46:53

tools are now good enough now that it's

46:55

beginning to affect the actual workflow

46:57

rhythms of non-trivial percentages of

46:59

programmers. And that's a cool

47:00

interesting story. This essay is about a

47:03

science fiction dream. This is not an

47:05

inflection point for most people if

47:07

you're not a computer programmer. This

47:09

is not from here we get some rapid

47:11

takeoff. From here everything changes.

47:12

And I've seen article after article

47:14

after this essay came back, including

47:17

one, if you read my newsletter today and

47:18

get at calupport.com, I dissect an

47:20

Atlantic article that does so much vibes

47:22

on exactly this. I just don't think

47:25

that's an accurate way to think about

47:26

this. All right, interesting stuff is

47:28

happening to computer programming. This

47:30

is not an inflection point that AI is

47:32

about to rise over our heads and change

47:34

everything. Again, it's a task for which

47:36

these models are supremely well suited

47:39

and all this progress has been

47:40

incremental

47:42

but steady is to continue to refine and

47:45

update because it's the only place where

47:46

they're getting non-trivial monthly

47:48

subscription fees right now is honestly

47:49

in that space. So, I don't want to say

47:51

nothing's happening, but also I think

47:53

this essay is um it's alarmist and I

47:57

think it it he gets the technology wrong

48:00

and he mixes truth with fiction and

48:02

makes statements confidently that just

48:04

aren't right. So, there's a lot of good

48:06

reporting out there about AI. This is

48:08

not it. You could ignore this one. You

48:10

can ignore this one. So, I don't know.

48:12

There you go, Jesse. Did you see that

48:13

essay? Everyone sent me that essay.

48:15

>> I did not see it until I saw it in the

48:17

script. I mean he he wrote it in part

48:19

with AI

48:21

>> and you can tell I don't know I the

48:23

bigger thing not the bigger thing the

48:25

other story here is these essays on X

48:27

going viral is like definitely I think a

48:30

thing of the winner of 2026 and

48:32

obviously that opportunity is going to

48:33

get saturated and go away but remember

48:35

that Dan Co essay we did that was also

48:37

one of these X essays that went viral so

48:39

I think we're in this moment where like

48:41

you can go viral on X doing these long

48:43

form essays and I bet it's not going to

48:45

last past March it's going to get

48:46

saturated did and then that opportunity

48:48

is going to go away. But man, you're

48:49

going to How many YouTube videos do you

48:51

think are being made right now about how

48:53

to go viral with your ex essays? There's

48:55

probably so much content about this.

48:56

>> I know. I don't know. I don't like I

49:00

don't like to think of myself as an AI

49:01

skeptic, but like I see myself as an AI

49:03

realist. I I really want to ground

49:05

everything I do and what's actually

49:06

happening. I don't like this vibe

49:08

approach. Well, I love the fact how you

49:10

referenced on an earlier show as well

49:11

that you're doing all the reading with

49:13

your students from the past and you see

49:16

all the recurring themes.

49:17

>> Yeah, I the doctoral seminar I'm

49:19

teaching on super intelligence with AI

49:20

doctoral students. Yeah, these themes

49:22

are very powerful and they've come up

49:25

again and again and again. It's I mean

49:28

people doesn't mean they're true right

49:29

now. All right, let's hear from a

49:30

listener here. News and notes. Let's get

49:32

a note here. Um, we got an interesting

49:34

email that was related to the Olympics

49:36

which are just sort of ending as we

49:37

record this episode. We got an email

49:39

from Katie I want to read and then I'll

49:41

react to it. Katie says, "Um, I've been

49:44

following your work for years and has

49:45

helped me immensely in both my personal

49:47

professional life. So, thank you. I

49:49

thought of digital minimalism as I was

49:51

reading Ilia Malinin's Instagram post

49:55

after his heartbreaking solo performance

49:57

in the freekate a few days ago. He cites

50:00

quote vile online hatred in quote as an

50:02

impetus for his literal downfall. I

50:05

don't know if you saw that Jesse, but I

50:06

guess the quad god who's from Vienna.

50:10

He's around here.

50:11

>> Um fell during solo. Yeah. They said man

50:15

so hard. They said he there there's no

50:17

athlete who's more favored in his sport

50:19

than he was in his sport. But I the two

50:23

times I watched him he did not win a

50:25

gold medal. Um they got in the team

50:27

though. Uh all right, back to Katie

50:28

Zemo.

50:29

I was struck by this, especially in the

50:31

aftermath of Simone Bile's well

50:32

publicized experience in which she cited

50:34

similar demons. I would have thought

50:36

that elite athletes would have taken

50:38

note and begin to see social media and

50:41

really any media coverage of themselves

50:42

as far more of a liability than an

50:44

asset. No doubt an online present helps

50:46

with sponsorships and other business

50:48

deals. But is it worth it if it prevents

50:50

someone from truly achieving the highest

50:52

status in their sport? If elite athletes

50:53

will meticulously attend to their food

50:55

consumption, why do they seem hesitant

50:57

to limit their media consumption? It

50:59

seems to me that as sports grows and

51:01

becomes more competitive, the edge might

51:02

be less and less in workout plans and

51:04

diet regimes, but in the still

51:06

countercultural practice of social media

51:08

abstinence. All right, Katie, I think

51:09

that's a really good note. Uh, it is

51:11

going to happen. It is kind of happening

51:12

in elite athletics. The the coaches in

51:16

the front offices are realizing this.

51:19

I've had conversations with like

51:20

multiple GMs from the NBA. Uh I had, you

51:24

know, I talked with like the head of a

51:26

internationally ranked rugby team. Uh

51:29

athletes are beginning to at least the

51:31

the teams are beginning to realize, oh,

51:35

this is a huge edge in a sports setting

51:38

where small edges really matter. The

51:41

problem is the players are young and

51:44

they're addicted because they've been on

51:47

these things all the time.

51:48

and their whole life has often been

51:50

about just training for sports and it's

51:52

an anxiety producing type of life. they

51:55

don't have a lot else going on because

51:56

they have to focus so uh diligently on

51:58

the sports and so they use the phone as

52:00

like here's my escape here's my way to

52:01

numb here's my way to self-medicate and

52:04

it's better than actual drugs right or

52:06

alcohol because I'm a I need to keep my

52:07

body performing and they end up addicted

52:09

and it's really hard for them it's why

52:11

for example from what I hear talking to

52:13

sports executives the biggest issues are

52:14

are in the NBA why youngest players you

52:18

have the smallest gap from you know like

52:20

high school you can go right from high

52:21

school into playing for an NBA team

52:23

compare this to something like major

52:25

league baseball where man it's a long

52:26

road even if you're like Eli Willitz and

52:28

you get you know recruited at 17 you're

52:30

going to go through all of these uh

52:32

minor league teams also the games are

52:34

played they're long and you don't have

52:36

technology with you uh so NBA has this

52:39

worse but anyways I think eventually

52:41

people are going to put their foot down

52:42

from a coaching perspective and realize

52:45

this is getting you you're going to be

52:47

better if you don't use this at all I

52:48

think it'll be a non-trivial advantage

52:51

and once elite athletes are doing it

52:53

this often is why I like This trend

52:54

often accelerates trends into the

52:56

general public. Just like there's

52:58

certain types of exercise and diet and

52:59

recovery routines that elite athletes do

53:01

that make their way down to how the

53:02

general public does it. This could have

53:04

a big impact

53:06

to hear like really top athletes say I

53:09

don't even touch that stuff and it helps

53:11

means more people who aren't elite

53:13

athletes might be like okay that's not

53:14

so eccentric anymore. One person who

53:17

does do this is Alex Hnold the the rock

53:21

the climber. He's talked about this a

53:23

lot because for him it's not just if I

53:26

lose a 5% edge uh I'm going to have a a

53:30

bad performance in a basketball game.

53:31

It's like if I lose that edge I could

53:32

fall and die. So he goes on like a very

53:34

long period in the leadup to his free

53:37

solo climbs where he doesn't look at a

53:39

phone, no social media, nothing so that

53:41

his head can just get clear and he can

53:42

get into this like mind space where he

53:44

can concentrate more. More athletes have

53:46

got to follow this. I mean, especially

53:48

like these Olympians, these young

53:49

Olympians, it just gets in their head.

53:52

Like, especially if you're like a if

53:55

you're going to wear what you have to

53:56

wear as a figure skater, you don't want

53:59

to be on social media. If if if you look

54:02

like you're in Blades of Glory, like you

54:04

do look like the character from Blades,

54:06

like you don't want to be on social

54:07

media. Just do your quad jumps, you

54:09

know? So, I think Katie is right. I

54:11

think we are going to see that trend,

54:12

and I think that's good. Did you watch

54:14

any of the Alex documentary on climbing

54:16

the skysa?

54:17

>> I watched it live. Watched it live. Um,

54:20

and then I watched it kind of was a

54:21

bummer. I watched a video of a

54:24

professional rock climber talking about

54:26

it and he was like, I can't emphasize

54:29

how easy this was. He's like, this is

54:32

not this is this is a not a challenging

54:36

climb for Alex Honold.

54:37

>> That kind of goes with your theme of,

54:39

you know, watching 30 minutes of a movie

54:40

and then reading a review. It did change

54:43

my experience. Yeah. Yeah. It was

54:44

interesting. But yeah, but basically

54:46

they put it on the rating and it was

54:47

like a relatively low rated climb. He

54:49

was like the only He said you could do

54:51

this like if you repeated this a

54:53

thousand times maybe he falls once but

54:56

probably zero times. Like for Alex it's

54:58

like for us if someone was like I want

55:01

you to climb this step ladder and you're

55:04

like yeah I can climb the ladder like

55:06

I'm not going to fall or whatever. It's

55:07

like they they said the main thing is

55:08

just um making sure that you had the

55:10

right uh make sure that you were trained

55:13

up enough you don't get arm fatigue.

55:14

>> Mhm. It was like 70 minutes long. I

55:17

basically fast forwarded so it only took

55:18

me like 20 minutes of I got the gist.

55:20

>> I was chilling with some friends and

55:21

then we just had it on. Yeah. I was at a

55:22

friend's house for his birthday. We kind

55:24

of had it on the iPad just like hey does

55:25

he fall? No. All right.

55:28

>> The scariest part was really the end.

55:30

>> You see the end?

55:30

>> Yeah.

55:31

>> He's standing on that little thing with

55:32

those winds up there.

55:34

>> I mean

55:35

>> but then he went on his phone. Right. I

55:36

wonder if he went on social media. He's

55:37

like, "Oh, I finally got here. Let me

55:38

get on TikTok."

55:39

>> He was like, "Oh my god." And then he

55:40

fell.

55:43

That'd be bad for him. Be good for us,

55:45

though. Right. Metaphorically. Alex

55:48

Honold publicly on live TV falling to a

55:51

gruesome death while his wife was there.

55:54

Be good for our views. We do well. Kind

55:57

of a bummer that didn't happen.

55:58

>> Just kidding.

56:00

It's kind of a bummer. Um, all right.

56:02

Let me do another note. Quick update on

56:04

my book. Right. So, as longtime watchers

56:06

and listeners know, my next book, which

56:07

I actually it's taking me much longer

56:10

than I thought, is I'm writing a book

56:11

about the deep life because I have this

56:13

idea that uh like when it came to

56:16

distractions, digital distractions in

56:18

the office, what actually worked is when

56:19

I wrote a book called Deep Work that

56:21

said, "Yeah, distractions are bad, but

56:22

what I want to give you is a bigger,

56:23

better offer." So, books that were just

56:25

about email being bad don't sell as well

56:27

as the book that was here's what you

56:29

should do instead. I realized I needed

56:31

something similar for our digital lives

56:33

outside of work. It's hard to tell

56:35

someone to get off their phone when the

56:38

life outside of the phone is sort of uh

56:40

unsettling or uneasy or anxiety

56:42

producing or just boring. So, you need a

56:45

bigger better offer. We don't need to

56:47

hear more about why the phone is bad. We

56:49

need to create lives that the phone is

56:50

not that interesting. So, that's what

56:51

the deep life is. I talk about it a lot

56:52

on this show. Anyways, the update,

56:55

Jesse, is I I handed in my manuscript.

56:59

So, I finally finished a draft of the

57:01

entire book. It's in the hands of of uh

57:03

my US and UK editors right now. There's

57:05

still a lot of work to be done after

57:06

that. Like significant rewriting happens

57:08

during the editing phases, but still

57:10

symbolically to get a complete

57:13

manuscript that it's like, "All right, I

57:14

got my arms around it." So, I'm pretty

57:16

psyched about it.

57:17

>> Can we talk about the conclusion and

57:19

your strategy with that or is that

57:21

>> Yeah.

57:21

>> top secret?

57:22

>> You mean my conclusion that I haven't

57:23

written yet?

57:23

>> Yeah. Yeah.

57:24

>> I feel like the audience would love

57:25

that.

57:26

>> I So, you're right. I didn't submit the

57:28

full manuscript. I submitted the

57:29

manuscript minus the conclusion. But

57:31

I've done this before because the point

57:34

is this is just like a bookw writing

57:36

thing, but that's the last thing you

57:37

write. And typically when you finish a

57:39

whole manuscript and I was like, I

57:40

wanted to get it done before I went on a

57:42

trip. The conclusion is kind of rushed

57:44

and they're bad because of that. And I

57:46

find it's much better to like finish a

57:48

whole book, step away from it for a few

57:51

weeks, clear your mind, maybe even get

57:53

edits back, and then say, "I'm going to

57:55

write the conclusion." And if the

57:57

conclusion is the only thing you're

57:58

writing and you've cleared your brain

57:59

and you're no longer exhausted, then

58:02

you'll write a really good conclusion.

58:03

But if it's the last thing you're

58:04

writing at the very end of like a really

58:06

hard push, conclusion isn't that bad. So

58:07

I I handed the whole manuscript except a

58:09

conclusion and I said, "Look, I'm going

58:11

to take a couple weeks and then I'll

58:13

tack the conclusion on the end." So

58:15

that's my I also leave the introduction

58:17

towards that was the last thing I wrote

58:18

before I submitted it was the

58:19

introduction. Um over the summer when

58:22

you were abroad for the month or not

58:24

abroad but just away you had written a

58:26

part and then had to throw it away.

58:28

>> I threw away a lot of that book.

58:30

>> Did that happen multiple other times?

58:31

Like

58:32

>> I've thrown away a lot a lot.

58:35

>> Is that typical with books or

58:36

>> It just depends for me. This one I This

58:40

one I I've thrown out as many words as

58:42

I've written like as I just submitted

58:44

I've thrown out at least that many

58:45

words. And there's a lot of that. The

58:48

first approach to the book wasn't right.

58:50

Um, so I threw that out. The second

58:52

approach was the right approach, but the

58:53

the way I was writing it wasn't right,

58:55

so I threw out a bunch of that. Um, some

58:57

of that stuff I salvaged and could use

58:59

in other places. But so

59:01

>> a lot of Brandon Sanderson has a good

59:03

quote about this, by the way. U, you

59:05

might know Brandon Sanderson as the

59:06

author of Name of the Wind.

59:10

Actually, you know, my son, my middle

59:12

son is reading a lot of Sanderson.

59:14

>> Oh, nice. He he's he just finished the

59:16

third book in the misborn. I told him

59:19

about the storm something. I don't know.

59:22

I don't know what S. Well, the storm

59:24

something way of kings. I don't know.

59:26

But his other like major like epic one.

59:28

He's like, "Oh, I got to read that." Uh,

59:30

but I was listening to Ferris's

59:31

interview with Sanderson again, which is

59:33

like a great interview. And he said,

59:35

"This is the big divide between amateur

59:37

and profess professional writers.

59:38

Amateur writers don't like to throw out

59:40

chapters, and professional writers do it

59:42

all the time. It's like I guess I'm a

59:43

professional because I threw out a hell

59:44

of a lot of chapters. It's like this is

59:46

good writing, but it's not the right

59:48

writing and then you got to throw it

59:49

out. But I think this book's going to be

59:51

good. It's a handbook. I mean, I really

59:53

wrote it like a handbook. I mean, it's

59:54

like it's practical. It's linear. This

59:57

builds on this, builds on this, builds

59:58

on this. Um, it's really meant to be

60:02

let's talk about cultivating a deep life

60:06

so your phone's less interesting as like

60:08

a engineering challenge. Like let's be

60:10

like very systematic about it. So, Slow

60:12

Productivity came out in 2024, I think.

60:14

In spring.

60:15

>> When do you think this one will

60:16

eventually come out?

60:17

>> A year from now.

60:18

>> So, spring of 2027.

60:20

>> Yeah.

60:20

>> Okay.

60:21

>> Yeah.

60:22

>> And then you'll do like a book tour and

60:23

everything.

60:23

>> Yeah.

60:24

>> Similar as last time.

60:25

>> Yeah. I will be I will be out and about

60:29

book touring it up and doing all our

60:31

doing all of our things. We did a

60:32

podcast here. That was We did a live

60:33

podcast here in Tacoma Park. That was

60:36

fun.

60:36

>> Uh we did Pollocks and Pros around here.

60:39

Did you come to that one?

60:40

>> Yeah.

60:40

>> Yeah. That was fun. We got a big crowd.

60:42

Um, went to LA, went to Austin. Do the

60:46

stuff. We'll do the stuff. All right.

60:48

Uh, finally, what am I reading? I

60:49

finished two books on vacation and I'm

60:51

doing the count, Jesse. This gets me up

60:52

to four for February because I know you

60:54

don't trust me anymore. And I'm almost

60:56

done with my fifth. So, we're recording

60:57

this. What's the date? Like the 18th.

61:00

>> Yeah,

61:00

>> I'll finish my fifth probably tomorrow.

61:02

>> I believed you. I just wanted to keep in

61:05

the audience.

61:05

>> You don't trust me at all. You think I'm

61:07

trying to pull a fast one. Um, all

61:08

right. So I finished on vaca on I

61:10

finished a book I had started before. So

61:11

we went to the Florida Keys for a long

61:13

weekend. Um I finished a book a new book

61:15

called attensify like at like a mix of

61:19

attention intensify. It's like a splashy

61:21

new like manifesto. It's a collective of

61:23

academics who are thinking and writing

61:26

about attention and the attack on

61:27

attention from digital devices. And this

61:29

is their their um big new bold book. Um

61:32

it's smart actually. It's smart writing.

61:35

Yeah. Um, I actually there's there's a

61:37

couple ideas in there I'll probably talk

61:40

about, maybe make a future deep dive

61:41

about, but that was a smart book. Uh,

61:44

some some definitely some good ideas.

61:46

Um, and then the thriller, I needed a

61:47

thriller to read when I was in the Keys,

61:49

and I needed to be related to that part

61:51

of the country. So, I found a Lincoln

61:54

um, uh, Preston and Child's

61:57

Gideon Cruz thriller called The Lost

61:59

Island, which takes place in the

62:00

Caribbean. It's a little nuts. It's a

62:04

little nuts. Uh the it was good set

62:08

pieces. The structure was not great.

62:09

Like it was very disjointed. Um

62:12

interesting. I don't want to spoil it,

62:14

Jesse, but they're cyclopses.

62:18

And I didn't think and I wasn't a It's

62:21

not a fantasy book. Let's just say

62:24

there's a cyclops.

62:25

>> I have two quick questions.

62:27

>> Yeah.

62:28

>> Would you ever want to be an editor

62:30

>> or you just don't have any time, right?

62:31

You'd much rather write.

62:32

>> We would rather write. Yeah.

62:33

>> Yeah.

62:34

>> Yeah. Yeah.

62:34

>> But you talk to editors all the time.

62:36

>> Yeah. God bless them. I don't want the

62:38

job.

62:38

>> Cuz they have to read all the time,

62:39

right?

62:40

>> Yeah. Which seems like it's fun, but I

62:41

think the frustration would be is like

62:43

you get Here's here's the problem. If

62:45

you're an editor, you develop fantastic

62:47

taste because you all you're doing all

62:49

day long is reading. You know what's

62:50

successful, you know what's not. Like

62:52

you, you know, you're just so good at

62:54

assessing like what's good or bad. And

62:57

like 80% of what you read, you're like,

63:00

"This is not great." You know, that's

63:02

the problem. Like you occasionally get a

63:04

book you're like this is great but you

63:06

you know too well why the stuff that's

63:08

not great is not great and I think

63:09

that's got to be

63:11

>> but what can you it's not your book.

63:12

>> Yeah.

63:13

>> So you're like I'll help the author but

63:15

like I would have written this book

63:17

completely differently. I think that's

63:18

got to be frustrating.

63:19

>> Yeah.

63:19

>> Um also they put too much work on

63:23

editor's plates right now. So it's like

63:25

I I think I wrote about this in a world

63:27

without email.

63:29

uh digital technology like email changed

63:33

the structure of the job of being editor

63:34

in the sense that it and personal

63:36

computers they added like seven or eight

63:39

more parts of the book publishing

63:40

process onto the plate of the editor

63:42

like now like you're involved much more

63:45

and more constantly in marketing and

63:47

sales and book shipping and fulfillment

63:48

and the cover design and all the you're

63:50

in the mix on everything and because of

63:53

this it's become a much more like admin

63:55

overhead heavy like logistical nightmare

63:57

of a job.

63:59

Whereas, you know, 100 years ago, it's

64:01

like you had your manuscripts, you took

64:02

them to your house in the Hamptons, like

64:04

without the digital technology,

64:06

>> there was less you had to have your

64:08

hands in beyond like working on the

64:10

books. And editors don't publish more

64:13

book per editor now than they did pre-

64:14

email, but they're just they're just

64:16

more busy, right? So, it's one of these

64:18

things where on paper they're like each

64:20

of these new things email lets editors

64:22

do makes them more productive on paper

64:24

because it's how could it be wrong to

64:26

have more information or more say on

64:28

things, but in reality it doesn't

64:30

produce more good books. So, it's like

64:32

one of these classic case studies of uh

64:35

you think in the narrow this technology

64:37

will make people more productive, but

64:38

then you zoom out on the metric that

64:39

matters and it didn't. So, I think it's

64:41

a hard job. Um, but they're the cool

64:43

thing about working with editors, they

64:44

read so many books

64:46

>> is their like feedback is like on it.

64:49

Yeah.

64:49

>> You know, like you give it to a friend

64:50

or someone or like they're like, "Oh, I

64:53

like this or what about this?" And like

64:54

sometimes it's useful, sometimes not.

64:55

The editor like they see straight to

64:57

your soul. They're like this. Nope. Yes.

65:00

No. What were you doing here? You're

65:01

forcing that. Like because they're just

65:02

so good at it. So I love working with

65:05

editors. I don't think I could do the

65:06

job. I wouldn't be any good at it.

65:07

>> And then last question. Did you read the

65:09

Rogan article in the New Yorker?

65:10

>> Remnix.

65:11

>> Yeah.

65:12

>> Yeah. Did you read it?

65:13

>> Yeah, I read it.

65:14

>> Yeah. I got that that issue kind of

65:15

late, so I only read it more recently.

65:18

Um, yeah, it's pretty good.

65:20

>> I I just We're talking about off off air

65:22

a little bit. I the idea of Rimick

65:25

listening to like these Rogan episodes

65:28

where,

65:29

>> you know, the moon landing is fake and

65:31

like some of the more extreme Rogan

65:32

episodes like, oh man, that's that's

65:35

funny. But Rogue is a compelling

65:36

broadcaster, so it's not like the

65:37

hardest job. I thought it was a pretty

65:38

good profile. The main thing, here's

65:41

what I've noticed. I think the the sort

65:43

of elite writer world that I'm a part

65:46

of, like the in the academic elite

65:49

world, like the biggest problem they

65:52

have with Rogan is it's our frame. It's

65:56

like our frame for seeing the world is

65:57

very much a like rationalist

65:59

intellectual frame. Everything is about

66:00

ideas and knowledge and argument. And so

66:03

like Malcolm Gladwell did a big thing

66:05

about this. Rimnick was really upset

66:07

about this is like why your job you like

66:10

Joe Rogan is to um be looking for wrong

66:13

information and pushing back on wrong

66:15

information and building correct

66:16

structures of epistemology and knowledge

66:18

or whatever. It's actually not the way

66:20

that most people approach the world.

66:21

Most people approach the world like Joe

66:24

through like social relations like

66:27

connection with people like these type

66:29

of things. um emotional reactions.

66:32

What's interesting? What's not

66:33

interesting? Uh this makes me upset.

66:36

This makes me happy. This is, you know,

66:39

makes me feel good. Uh I want to like be

66:43

a a leader and a friend. It's like all

66:45

these things that are, you know, pre

66:49

writing rationalist, post-enlightenment

66:51

type of thinking that all like our elite

66:52

people do. And so they just see it very

66:54

differently. Like bro's like, "Oh,

66:55

someone's here. I want to like connect

66:57

with them and see if I can generate

66:59

interesting emotions or like I want to

67:00

something that's going to catch my

67:01

attention. But if it's like Rimnik or

67:03

Gladwell or me, our instinct is like the

67:06

world the reality is shaped by structure

67:08

of information and you cannot deform

67:11

that structure of information in like

67:13

incorrect ways. And if someone is saying

67:15

something incorrect, you have to push

67:16

back on it. Then there's also like blind

67:18

spots in it too because it's it becomes

67:21

more if the people are saying something

67:24

incorrect on the things I really care

67:26

about, you better push back on it. But

67:28

if it's like something where it's like,

67:30

okay, yeah, this is incorrect

67:31

information, but like it's

67:34

thematically I get what you're getting

67:37

at. I'm with you on that. Like that's

67:38

fine, right? So it becomes a little bit

67:40

sele I'm just critiquing my own circle

67:42

here. gets a little bit selective where

67:44

you know it might

67:45

>> it might be like oh thematically we're

67:47

not going to get mad at something that

67:48

maybe is like making a a strong

67:50

progressive point but in doing so is

67:52

being loose with facts and reality and a

67:54

lot of commentators from like the elite

67:56

circles will be like yeah but like

67:57

thematically that point is right so

67:59

that's fine but if you are on like some

68:01

health topic or something like you're

68:03

getting at thematically this point of

68:05

whatever we should we trust big medicine

68:08

too much but your facts are wrong it's

68:09

like how can you not stop that person so

68:11

we we all blinders on as well. Um, but

68:14

it was a good profile and well written.

68:16

He's a good writer as a Pulitzer.

68:18

>> All right, I think that's all the time

68:19

we have for today. Thank you for

68:21

listening and watching. We'll be be back

68:23

next week with another episode. And

68:24

until then, as always, stay deep. Hey,

68:27

if you like today's discussion about how

68:29

to pay attention throughout an entire

68:31

film, I think you might also like

68:33

episode 390, which looks at what happens

68:36

when real people stepped away from their

68:38

smartphones. Check it out. I think

68:40

you'll like it. But here's an idea that

68:42

I've longed to believe. It's not enough

68:45

to just list the harms. The problem is

68:48

that phones also have legitimate uses.

Interactive Summary

The video discusses the increasing difficulty people, particularly students, have in paying attention to feature-length films, attributing this to the impact of digital technology and smartphones. It explores the concept of 'cognitive patience' and how constant phone use degrades this ability by over-stimulating the brain's short-term reward system and weakening its long-term reward system. The speaker offers practical advice on how to become a better movie watcher, including removing phone distractions and actively engaging with the film through scene-by-scene analysis or reading reviews. The video also touches upon a viral essay about AI, critiquing its alarmist claims about rapid advancement and job displacement, arguing that the progress is more incremental and focused on specific applications like programming. Finally, it includes a listener's email about elite athletes abstaining from social media to improve performance, drawing parallels to the importance of digital minimalism for mental clarity and focus.

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