0:00

Over the last twenty five years the world

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has witnessed incredible progress from dialup modem survive

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G connectivity from massive Pc towers to a

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I enabled Microchips innovators, a rethinking possibilities every

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day through it all in West Coast Qq

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each yeah has provided investors access to the

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next twenty five years of new ideas by

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innovative companies Invesco, Kinky Kill Let's rethink possibility

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tech sector or some Twitter, as can relativity

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the more diversified investments. Before investing, heavily beaten

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consider fun investment Doctors risk started expenses and more

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in perspective that invesco.com invesco distributors and. What's.

0:36

Going on with you? Well you know I'm

0:38

having sort of a weird week. So I

0:40

came in on Monday him and to the

0:42

office of the New York Times, the San

0:44

Francisco and someone said there's and there's a

0:46

naked man outside the office who's ranting and

0:49

I said well, how is care. About

0:54

aware that you should know that weekly podcast

0:56

on Wednesdays and on Mondays and then. And

1:00

then I learned that I was actually the part of

1:02

the seat stupid day parade you know about. Way I've

1:04

not heard of this. This is. Apparently an annual

1:06

tradition in San Francisco where some big goofballs

1:09

get together on April Fools Day April first

1:11

and they parade through the streets of San

1:13

Francisco holding like nonsensical signs and some of

1:15

them apparently are naked eye and this is

1:18

what was going on. I love this town

1:20

so much there's a tell it as a

1:22

cell back and fix it happened in San

1:24

Francisco you wouldn't even believe and they're wonderful.

1:32

I'm Kevin or it's A on us

1:34

to New York Times. I'm Casey Noom

1:36

from Platform Or and this is our

1:38

for this week How Ai is affecting

1:40

the economy. Ten artist Paul Trillo joints

1:42

to discuss how we used Open the

1:44

Eyes Sore Actual to explore the future

1:46

of filmmaking, and finally a cyber sneak

1:48

attack that could have brought down the

1:50

web was caught. In the nick of

1:52

time. not by govern, not by me, A

2:07

before we get a nursery this week we just

2:10

wanted to remind people were on you tube some

2:12

always talk about in the so this week is

2:14

going to be better to see them to Here

2:16

we're gonna talk with someone who uses a I

2:19

to make films If you'd like to watch those

2:21

films are frankly if you'd like to watch the

2:23

podcast instead of just listening to it's you can

2:25

go to Youtube channel on youtube.com/hard Fork or deserves

2:28

Hard Fork on you tube. Aren't know?

2:30

Onto the shell. Casing this

2:32

week I want to talk about A I

2:34

and Jobs because this is a topic that

2:36

we get asked about all the time by

2:38

listeners of the show that I hear about

2:41

all the time from readers. Is this technology

2:43

that you guys are always talking about? Actually

2:45

going to take people's jobs is a good

2:47

to help people at their jobs. And how

2:49

long do we have to wait before our

2:51

jobs? Your jobs get affected by all this

2:54

stuff. That's where and when Blisters as we

2:56

always say. don't worry if we find out

2:58

that A is gonna take your job we

3:00

will email you individually and until then he

3:02

said well as websites Cbt, Emily's as befits

3:04

so I thought we should. said. Break.

3:07

This out into a couple pieces. One of them is

3:09

sort of. About. The Present: What

3:11

do we know about how Ai is

3:13

already affecting jobs and companies and their

3:15

plans to employ or unemployed people in

3:17

the near future? And and then I

3:19

think we should talk about some of

3:21

the various theories that are coming out

3:23

about how and whether generative A I

3:25

Will actually leads to major seems is

3:27

in the job market the right? Let's

3:29

do it. So this story I'm is

3:31

by my colleagues Jordan Home and and

3:33

genius my like it's called will Ai

3:35

boost productivity Companies for Hope So And

3:37

it's sort of a survey of what's

3:39

going on. Out there in the world,

3:41

at companies like Walmart and Wendy's and

3:44

Abercrombie and Fitch which is apparently using

3:46

a I to write and product descriptions

3:48

an answer trying to take stock of

3:50

like, what effect does all this cumulatively

3:52

having on the economy and the job

3:55

market? Well, And I'm curious about this

3:57

because there was that story the other

3:59

week about how Wendy was thinking about

4:01

during surge pricing and that was sad.

4:03

repeat. his idea is the bad rap

4:05

and I have yet so digging into

4:08

the data a little bits of so

4:10

far, it just seems pretty early for

4:12

any of this to start showing up

4:14

in official economic statistics, but we do

4:16

see in some of the most recent

4:18

data a bump in productivity and this

4:21

data has been a little volatile since

4:23

covert, But some economists are starting to

4:25

wonder if this is real and if

4:27

this productivity increase might actually stick around.

4:29

Okay, In addition to that sort

4:32

of aggregate data that economists can see

4:34

at the national level of, there's also

4:36

just been a bunch of examples of

4:38

companies that are starting to use entered

4:40

of Ai in some cases to pair

4:42

jobs among their own workforce. So I

4:44

recently duolingo the company that makes the

4:47

language learning app not to be confused

4:49

with do a Lipo dresses and Er

4:51

has Min Suk let her out at

4:53

another, had us and yes you the

4:55

best of duel lingo or recently said

4:57

that it was cutting about ten percent

4:59

of it's contractors. Are Not. Laying

5:02

off any full time employees, but basically

5:04

just at in a paring down the

5:06

number of people it needs to create

5:08

content. A spokesperson for the company said

5:11

we no longer need as many people

5:13

to do the type of work some

5:15

of these contractors were doing. Part of

5:17

that could be attributed to a I

5:20

U P S recently cut about twelve

5:22

thousand managerial jobs. The Ceo I mentioned

5:24

how ai machine learning and could reduce

5:26

the need for pricing experts among other

5:29

jobs, but they've also said they're not

5:31

replacing workers. With a i've. Been

5:33

there was the company Florida which is one of

5:35

the things didn't do. Not far enough actually do

5:37

know corner foreigner is one of these by now

5:39

pay later companies have they have said that their

5:41

Ai assistant did the work of seven hundred customer

5:44

services. I'm always so curious though when I hear

5:46

that it's like yeah I'm for from foreigners perspective

5:48

it's great but I would love to hear from

5:50

the people who actually had to use the Ai

5:52

chat bots. Do you think it was as good

5:54

as a person whom I've used to this A

5:56

I chat bots and I'll say I think people

5:59

are better. Coroner said in their

6:01

experiment that they actually found that the Ai

6:03

chat bots were rated just as good as

6:05

the human agent all right, and that they

6:07

solve their problems faster. So these

6:09

are the kinds of experiments and test the

6:12

we're starting to see play out at various

6:14

companies. We haven't seen sort of mass layoffs

6:16

yet as a result of generative A Ice,

6:18

but these are the kinds of experiments you

6:21

would expect companies to be running on this

6:23

technology trying to figure out where can we

6:25

save down you know, maybe you know thirty

6:27

percent of the the accounts payable department or

6:30

maybe a few engineers who we may be

6:32

don't need anymore and replacing those people with

6:34

a i Will It as A is A

6:36

is a read through. All of us have

6:39

been. I find myself wondering if maybe there

6:41

never will be a mass layoff moment at

6:43

these companies. Maybe it will just be a

6:45

steady erosion as they figure out bit by

6:47

bit how to make do with fewer of

6:50

your people. You know This is sort of

6:52

one of the fascinating things that I'm observing

6:54

as I go out and talk to people

6:56

who run businesses you have. No one wants

6:58

to be seen as sir have a heartless

7:01

capital as to is just like you know,

7:03

wantonly are laying off workers and replacing them

7:05

with robots. but they are doing a lot

7:07

of things around the edges to try to

7:09

may be so lay off people for assistance,

7:12

see and then replace some of those people

7:14

not with other people but with software that

7:16

have it both ways defined. a signal to

7:18

Wall Street. Hey look look at how clever

7:20

were being and how much more efficient were

7:23

getting and how much worth cutting costs with.

7:25

are trying to avoid the Pr backlash that

7:27

Woods couple I when they say that we

7:29

no longer things humans have value in the

7:31

enterprise exactly. One. Of things have been

7:34

really surprising to me is the reluctance that

7:36

some corporate leaders have been having to pay

7:38

embrace this new Ai technology and use it

7:40

to replace workers even when the technology is

7:42

fully capable of releasing the workers. So I

7:45

had a conversation a few months ago with

7:47

a guy of were met at a at

7:49

an Ai event he he runs a big

7:51

commercial real estate from they be developed real

7:53

estate all over the country and he was

7:56

telling me that you know for years he's

7:58

had these junior analysts who will. Go

8:00

out the visit various cities you know and

8:02

they'll come back and or produce reports about

8:04

the local commercial real estate market in those

8:06

cities you go to Jacksonville and it'll come

8:09

back with a ten page report about all

8:11

of the various commercial real estate friends in

8:13

Jacksonville News and he said basically once had

8:15

C B T came out he started giving

8:17

those assignments to chat bots and seen whether

8:20

they could do them any. Found that the

8:22

reports it's had to be T would give

8:24

him about the local real estate markets wesley

8:26

better than the ones his junior analyst were

8:29

giving him. And. So I

8:31

said, well. Okay so then what

8:33

happens to the junior analyst like dude just lay

8:35

them off and replace them all with a I

8:37

and he said something that for a surprise me

8:40

which is no because that's how they learned the

8:42

job so he was not. Just. Doing

8:44

these junior analyst has sort of you

8:46

to help or monkeys who go out

8:48

and produce these reports see viewed this

8:50

process of going to a city, getting

8:52

on the ground, talking to local businesses,

8:54

examining the real say market up close.

8:57

As. A part of the training process and

8:59

how he builds sir future leaders for his

9:01

business. He basically was telling me like yes,

9:03

I could replace those people with a I,

9:06

but then I'm actually cheating myself in the

9:08

long run and I think that's one of

9:10

the kind of intangible things that is hard

9:12

to get when you just look at kind

9:15

of. Overall economic data is like. There

9:17

are many reasons that people have. Jobs.

9:19

At their companies have and there are many

9:22

types of. Serve incentives that are operating

9:24

at these companies. and so even if it

9:26

is sort term profitable to replace a bunch

9:28

of people with a eyes, there might be

9:30

other reasons that you don't want to do

9:32

that. So I think that's part of what's

9:34

going on his that makes us to me.

9:36

But I would also just note that we

9:38

are still sort of in this very early

9:40

phase with Generated A I were If you

9:42

believe the people working at the big companies

9:44

making the largely was models, they're telling us

9:46

within a generation or two it's these models

9:48

are going to be exponentially better. and then

9:50

I wonder if some of that feeling of

9:52

need to keep. His people around and train them

9:54

so they can take on the next job up

9:56

the ladder. I wonder if that feeling starts to

9:58

diminish? It's possible it's all. If. He

10:01

thinks to make mistakes are still not totally

10:03

predictable. They're still pretty weird, frankly, and so

10:05

you might not wanna throw them into the

10:08

core of your business right away. At least

10:10

not without a lot of supervision. So that's

10:12

kind of. Where. We are now

10:14

today in the job market with a

10:16

I. We have lots of companies running

10:18

lots of experiments, spending lots of money,

10:20

hiring lots of consultants, trying to figure

10:22

out how can the stuff make us

10:24

more productive. We don't see it kind

10:26

of it in the economic data just

10:28

yet, but there are signs that people

10:30

are starting to figure out ways to

10:32

use the stuff to automate jobs. absolutely,

10:34

but you know, Cabinet the same time

10:37

we're starting to seats studies that suggest

10:39

that perhaps the middle class will actually

10:41

thrives in a world where generative a

10:43

Ice is ascendant. Am I think that

10:45

finding surprise us A we should talk about

10:47

this year. So there was an interesting a

10:49

paper that got written up this week by

10:51

my colleague Steve Laura The Times that was

10:54

based on the up some work by an

10:56

economist at Mit named David. Artur. Davis is

10:58

someone whose work I've been falling for a

11:00

long time. He's one of my favorite economists

11:03

who looks at a I and the labor

11:05

markets and. Last. Month he

11:07

came out with a paper that had

11:09

what I would consider like a pretty

11:11

contrarians ceases which is that he actually

11:13

thinks that a I could if used

11:15

well assist with restoring and of the

11:17

middle class of the labor market that

11:19

has been hollowed out by things like

11:22

automation and globalization move more one that

11:24

be nice to fix. Yeah so basically

11:26

his arguments is it's not that he's

11:28

like observing this is already happening, this

11:30

is a sort of something he thinks

11:32

will happen Which is that basically you

11:34

have this economy now where you have.

11:36

Kind of like a eat a

11:39

missing Middle East or have like

11:41

wage workers and people who are

11:43

lower earning workers and then you

11:45

have kind of this expert class

11:47

of people who in make decisions

11:50

about you know medical decisions, legal

11:52

decisions of corporate management decisions and.

11:55

That one of the affects the

11:57

Gen I could have is basically

11:59

empowering a lot of people at

12:01

the bottom the end of that

12:03

market of that labour markets to

12:05

develop the kinds of expertise and

12:07

make the kinds of decisions that

12:09

previously required at highly paid professionals.

12:11

So one example he cites in

12:13

this paper is. Nurse

12:15

practitioners. That's. A relatively

12:18

new occupational category, there used to

12:20

be nurses and doctors, and then.

12:22

Several. Decades ago, they started to

12:24

practice at exactly exactly speed. Basically

12:27

developed this kind of middle tier

12:29

of medical professionals who were not

12:31

full doctors. They didn't go to

12:33

medical school, but they were qualified

12:36

to do things like write prescriptions

12:38

and make certain recommendations about your

12:40

health care. And so what David

12:42

Autor argues is it. Basically. A

12:45

I could allow non experts in

12:47

lots of different fields to kind

12:49

of develop the expertise and the

12:52

decision making capacity to basically take

12:54

on the nurse practitioner equivalent in

12:56

whatever their industry is. So maybe

12:58

you have paralegals who. Are.

13:00

Armed now with all the center to be I

13:03

who can actually start to make the kinds of

13:05

decisions they might have required a full lawyer before.

13:07

That's exciting. I'm imagining using sad Cbd, become like

13:09

a pair of firefighter where I can just sort

13:12

of read about how to do it and then

13:14

call down to the scene and as be like

13:16

that may and point of my resume or over

13:18

there that's exactly what you call you call the

13:20

fire department because your house is on fire and

13:23

are like well we could get a firefighter there

13:25

but it's gonna take you know an hour at

13:27

we do have Casey. ah he's got he's got

13:29

a tattoo pretty subscription. And a hose and he's ready

13:31

to go. He could be there and five minutes. Systemically

13:34

that if you have it says he beauties of

13:36

prefer the housing a very fighters like sisters I

13:38

would be like a Paris the Iau you know

13:40

where it's like you sort of have the fat

13:42

salary and the prestige but were able to do

13:44

it with only half the trainings and you know

13:46

you are mostly does asking questions have a chat

13:48

bot which as far as i can tell us

13:50

mostly what see as are doing any way. Through

13:53

the i mean this is this is one

13:56

exciting possibility I think and I I I

13:58

love David are tours op. Them about

14:00

your restoring the middle class through Jenner

14:02

they ice. I think there are lots

14:05

of reasons it might not work In

14:07

practice, there's all sir licensing regimes in

14:09

various occupation, so it's like that. There

14:12

are some barriers to add the sort

14:14

of optimistic feature that David Artur envisions,

14:16

but it's just one sort of. Interesting.

14:20

Theory about where all this could be

14:22

had. Answer and I But I mean

14:24

I do buy something fundamental about that

14:26

which is that if you believe that

14:28

the as generative A I tools will

14:31

be com strain of counselors, coaches, guides

14:33

and there is a field that you're

14:35

interested in, this and that technology can

14:37

just kind of live alongside you understand

14:40

what you're working on, continually make suggestions.

14:42

It should actually accelerate people's rate of

14:44

learning and the development of their expertise

14:46

and I can see that having an

14:49

effect. On the middle class yeah, I think

14:51

that's that's server Optimistic vision. I do think that

14:53

there are a lot of people who are not

14:55

actually using a I to become better workers. They're

14:57

using a I to cut corners I'm and do

15:00

less work and in a we see this in

15:02

schools obviously with students to using the stuff that

15:04

seat. But there's also a lot of examples of

15:06

this happening out in corporate America to people you

15:09

know, maybe not using the stuff in the way

15:11

that would be most effective for them over the

15:13

long term, to saying like i've got a pretty

15:15

this report from my boss or there's and I've

15:18

gotta put together this powerpoint presentation. I don't feel

15:20

like doing it was a sled they I metal

15:22

a threat. But if there were more economic opportunity

15:24

that could come from using these things to develop

15:26

as what is perhaps more people would develop as

15:29

priests right now people are doing What you're saying

15:31

is because there's no economic penalty for them rights.

15:33

But ah, if there was an economic advantage maybe

15:35

they would use it. Yes it does improve with

15:38

what do you think companies should be doing with

15:40

centered of a Iran? Let's let's take like let's

15:42

take it out of our industry. And to say

15:44

like in a you run let's say I have

15:46

a big guy you know restaurant same yeah the

15:49

cheesecake. Factory reset Exactly like they make

15:51

the menu ten times longer. Outlet

15:53

for the villa in there a

15:55

a a a be like what's

15:57

companies be using this stuff for.

16:00

I think it depends what kind of

16:02

what what kind of company you are.

16:04

Honestly, if you're if you're running a

16:06

restaurant chains, I don't necessarily see that

16:08

there's a ton in there for use.

16:11

Maybe you want to experiment with some

16:13

copywriting? Maybe want to experiment with using

16:15

their the Image Generation test? Consider some

16:17

new advertising campaigns, but all that stuff

16:20

feels like you know, a minor and

16:22

experimental. As a another

16:24

he added maybe if you work for like a

16:26

copywriting from then maybe you want to be using

16:28

and a lot made, Then maybe you want to

16:30

be testing out all sorts of different models and

16:32

seeing which ones are. He is working better for

16:34

you. So I think that's kind of highly dependent

16:36

on the the kind of business that you're running.

16:39

But for the most part I would say you

16:41

want to manage your expectations Here is like it's

16:43

not going to be doing at a time for

16:45

you. I don't think you, I do, I do.

16:47

I. I think that this stuff is already. Pretty.

16:50

Good any and in certain sort of

16:52

out what? I. Mean so

16:54

much of our economy does runs on paperwork

16:56

and forms and reports and presentations. that's of

16:59

is some catnip that's low hanging fruit for

17:01

dinner of a see like like a story

17:03

the other day that was like there's a

17:05

company that's creating an Ai coworker like and

17:07

if you're in, if you're working on a

17:09

software company there's gonna be says character called

17:12

doesn't see them in the up. Very confusing

17:14

name. Yes, I don't like it. I believe

17:16

it's cognition. Yes the name of this company

17:18

that has working on it's he. Are you

17:20

know the idea is you know you're not

17:23

gonna have dire. As many engineers because now

17:25

you have Devon and of and can

17:27

like sort of help you write code

17:29

us that's a very early stages when

17:31

that gets good then. Okay yes now

17:33

a lot of people I think are

17:35

going to be using something like that

17:37

and as going to have a meaningful

17:39

affects our productivity stuck his I want

17:41

to and this discussion by talking about

17:43

our own experiences miss and and I'm

17:46

it doesn't work We do support one

17:48

another physicists So you've talked before with

17:50

me about how you have started experimenting

17:52

with using Gen Vi in your. Newsletter

17:54

I'm used to use at Center of

17:56

Ai to create the images that run

17:58

on top of some your. The letters

18:00

I've noticed you doing that less recently are

18:02

going to hear about why I'm You've also

18:04

talked about using it's user organize and collect

18:06

various links that you putting your newsletter. So

18:08

how is your own use of generative ai

18:10

at work or changed over maybe the past

18:12

year? So what I would say is I

18:14

truly have tried a bunch of things and

18:16

for the most part it has banned Marshall?

18:18

Start with the images but you're right. For

18:20

a year or so I was regularly using

18:22

a I generated images of the top of

18:24

my newsletter he added. The truth is I

18:26

just got a lot of feedback from readers

18:28

that they hated it. They. Felt like I was

18:31

stealing money from artist. They felt like you know

18:33

I was using models that had been improperly trailer

18:35

copyrighted material and they hated. seeing. as I have

18:37

some people say that they refused to subscribe like

18:39

because they swaths that I was using these images.

18:41

From my perspective, it had been a way to

18:44

enhance my own creativity because I can't draw, I

18:46

can't make anything look cool, but I can type

18:48

in a box and that's really cool to meet.

18:50

But I decided to take the note from readers

18:52

of For the most part, I've sort of taken

18:54

a pause on using that kind of generative a

18:57

That's really interesting because youth, it's not like you

18:59

were. The alternative with the you were

19:01

going to go pay a human artist to make

19:03

this stuff you were probably just gonna pull like

19:05

an image from Getty images are surprisingly that's what

19:07

I that's what I was going to do ano

19:09

I when I work on a very short deadlines

19:11

the idea that I could find the illustrator answer

19:13

a make it Happen inside interviewed it just wasn't

19:15

very likely. But at the same time you know

19:17

people were not excited to see the generative they

19:19

are images that's interesting L ot no more. Interestingly,

19:21

I think I have been able to with when

19:23

I finish my columns with some reasonable amount of

19:25

time before my deadlines actually take them to some

19:27

of the large language model at us. A critique

19:29

This it. The idea is not necessarily that

19:31

it's going to make Mike Hulme hundred times

19:33

better, but. You. Know, I think all

19:35

of us writers if you could get feedback

19:38

from five or ten people before you publish

19:40

anything, you you might do it. And because

19:42

these things can analyze your work instantly. ah,

19:44

they're sort of no penalty for doing it.

19:46

I wouldn't say I've changed my writing a

19:48

lot in response to what I've heard, but

19:51

yes, it does catch grammatical errors, it does

19:53

taps typos and it's increasingly it's been able

19:55

to earth identified the tone of of however

19:57

writing about something and it's know sort of

19:59

asking me to did you mean it to

20:01

sound the Swiss What? that is The eerie

20:04

as part for me is I feel like

20:06

over the past year am I would say

20:08

Gemini Googles Gemini in particular has been the

20:10

one that has really been doing this. It.

20:12

Feels like it can get at the subtext.

20:14

Of what I my name's better than other things

20:16

in the past so those been interesting and I

20:18

do think I will keep doing it because you

20:21

know it went when you're right or that kind

20:23

of be back is a gift and I will

20:25

send you you centered of Ai at the New

20:27

York Times. So yeah we the New York Times

20:29

has some rules about using generative A I and

20:31

our allowed are not allowed to use it. You

20:33

know I'm not using it for journalism. I do

20:35

not write my columns which entered of a Ice

20:37

and I I. I frankly wouldn't do that even

20:39

if I were allowed to because I just think

20:41

that like that would be boring. I enjoy writing.

20:43

It's not like I don't I'm. Not eager to

20:45

turn that part of my job over

20:47

to dinner to be I, I have

20:49

basically found that it is the best

20:52

research assistant I've ever had. Some you

20:54

know now if I'm looking up something

20:56

for a column or preparing for a

20:58

podcast interview and I do consult with

21:00

centered of a I almost every day

21:02

for ideas and brainstorming interests. The things

21:04

like research like like new make me

21:07

at a time line of all the

21:09

major cyber attack newlands him years or

21:11

something like that and of course I

21:13

will fact check that research. Before I use

21:15

it in a piece. just like I would with

21:17

any research assistants and but that's the tennis thing

21:19

That centered of Ai for me has been really

21:21

good at. And I found it. Generally

21:24

I has actually changed my work in a

21:26

different way that I wasn't. Sure,

21:28

if perhaps expecting which is that is

21:30

is made me much more attentive to

21:32

the detail of my own writing and

21:34

trying to make sure that what I

21:36

rights does not sound like sad tbt

21:38

rodents because I think the moment as

21:40

a writer that you allow yourself to

21:42

drift in that direction you are giving

21:44

up your advantage. You are basically saying

21:46

I am replaceable. I am totally indistinguishable

21:48

from this sir generic text exterior and

21:50

I think this is that sounds actually

21:52

for the entire economy as more and

21:54

more of us have reason to use

21:56

generative A Ice. In our jobs is

21:59

how to use it to augment what

22:01

you do without making your boss think

22:03

that that augmenting technology could actually do

22:05

the whole job. I think that's a

22:07

really important topic. A I and Jobs.

22:09

I think we should continue to keep

22:11

tabs on it and in addition to

22:14

looking at said the economic data and

22:16

what economists the researchers are noticing about

22:18

kind of overall productivity. I would love

22:20

to hear what people's actual experiences of

22:22

using centered of a I successfully or

22:24

unsuccessfully at their own jobs. If you

22:26

are listening to this and you have

22:28

a really interesting story. About your own use

22:31

of Gen Vi at work or your company's experiments

22:33

with the stuff that if you they're gone super

22:35

well or super badly of I would love to

22:37

hear from you said send us an email or

22:39

Portland with a semi for that. I I particularly

22:42

want to hear from you if you tried. you

22:44

started of a i work in that when particularly

22:46

badly sister that sort of my own son of

22:48

a lot of sensibility as you have bloopers. I

22:50

mean. For

22:56

the break will take a look at a very different

22:58

part of it. I has been used Smith movies. Take.

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23:44

Hard for. I mean

23:47

A Martin the host of the Modern

23:49

Love podcast. In every

23:51

episode, repeat into an intimate corner

23:53

of someone's life and learn about

23:56

what love means to them. Thirty

23:58

five years with another. I've

24:00

never spent that much time with anyone else so

24:02

both kind of that. I love you pretty fast.

24:04

As long as they keep for dance up I'll

24:07

keep the dense Snc felt the same way. an

24:09

instant connection. It's a window

24:11

into how real people navigate all

24:13

kinds of. Love. I mean

24:16

romantic family friendship, dog

24:18

based. Their stories

24:20

of life changing moments small

24:22

do is. Big Revolutions. My

24:25

advice is that it's okay if

24:27

it's hard. A lot of the way that

24:29

you manifest your love. For your children is

24:31

some fucking and I'm under just looking

24:33

at them in or almost like wow

24:36

you know so much that I couldn't

24:38

even dream of knowing about my brother.

24:41

You can listen to Modern Love where

24:43

you get your podcasts. Okay,

24:47

that was very sober and rational discussion

24:49

about Ai in the labor market. and

24:51

now I want to get a little

24:53

weird. Let's please get a little weird.

24:55

So we've been talking for our weeks

24:57

about this new open a I video

24:59

generation tool called Sourav. This is something

25:01

that was demoed at Sam Altman was

25:03

Sir fielding requests on X. You tell

25:05

me whatever prompt you want to type

25:07

in disorder and all of see what

25:09

comes out of it's this is basically

25:11

doing for video what tools like Dolly

25:13

and me Juri did for still images.

25:16

It works much the same way as

25:18

one of these diffusion based models you

25:20

type in some tax. It gives you

25:22

back a snippet of video representing whatever

25:24

you typed. Yeah, and you hear that

25:26

and you think what you know we.

25:28

We know that making films is extraordinarily

25:30

expensive. It's very collaborative, it involves all

25:32

kinds of specialists, and the idea that

25:34

we might soon be in a world

25:36

where people can just type what kind

25:38

of movie they want to see in

25:40

a box and get something resembling that

25:42

feels like a big leap forward. So

25:44

whenever any new Ai tool or comes

25:46

out, my first question. Is always what can

25:48

I use it and for this tool sore

25:50

the answer was absolutely not Thought that the

25:52

people who weren't allowed to use this product

25:54

they called the sore losers. Up

25:57

Up Up Up Up Up. So

25:59

we couldn't. Actually use it to ourselves.

26:01

Open A I have not making this

26:03

public yet for various reasons but they

26:05

did put out a a blog posts

26:07

of showcasing the work of a bunch

26:09

of filmmakers who were given access to

26:11

the earliest versions of Sore Us and

26:13

so we're going to do the next

26:15

best thing today with his We're going

26:17

to talk to someone who has actually

26:19

been able to use or and play

26:21

around with it said. Today we are

26:24

talking with Paul Trillo. He is a

26:26

multi disciplinary artist and filmmaker who is

26:28

based in L A. It's I've seen.

26:30

Some has worked before with other Ai tools.

26:32

He's been playing around with the stuff for

26:34

a while now and organ talked him say

26:36

about what he learned, what has experience was

26:38

like and what he thinks. The implications for

26:41

Hollywood and some of the filmmakers out there

26:43

who are nervous about the stuff are that's

26:45

right. One of things were going to ask

26:47

him about his this short film that he

26:49

made with sore called the Gold and Record

26:52

which he made after being inspired by a

26:54

project that Carl Sagan undertook in the Nineteen

26:56

seventies to create a kind of audio time

26:58

capsule of humanity and broadcasted. Out into space

27:00

in the hopes that aliens would find it's

27:03

and listen to it and decide not to

27:05

destroy our entire civilization. We'll still far. Let's

27:07

say it has been successfully worked for. Delta

27:09

Record Worth hats off to call the and

27:11

the Go On record we should states is

27:13

a little hard to describe. It's a minute

27:15

long. It's kind of avant garde. You'll be

27:17

able to see it if you're watching this

27:19

on you tube. If you're just listening on

27:21

the podcasts, didn't go on the show notes

27:23

willing to at there as well. Alternatively, just

27:25

take mushrooms and think the Golden Record and

27:27

it'll be similar inside. surmise a specific. A

27:31

thing of all. Pulse.

27:38

Hello Welcome to Hard Forks! Oh Wow!

27:40

Thank you so much for having me

27:42

Mrs. Literally. The only

27:44

podcasts I can tolerate. A

27:48

Shock Jocks of Tax and It's sister

27:50

We We actually were recently voted that

27:53

most tolerable podcast which was regarded as

27:55

he have Few people have told us

27:57

they have. They've been a punch there

27:59

speakers After hearing the bad. So

28:03

paulo. I'm wondering if you could. Tell

28:05

us about the emotional experience of using

28:07

saw the first time you've typed in

28:10

a prompt into this tool and got

28:12

back a video. Do you feel

28:14

any things. I mean. I.

28:17

I was shocked I was floored. I

28:19

was confused I what I was like

28:21

a little bit unsettled because I was

28:24

like damn this is like doing things

28:26

that I didn't know it was capable

28:28

of. Steam Member: what the the first

28:30

thing you tried was that you the

28:32

has a reaction with. The first

28:35

one that really took me out

28:37

of it was the video that

28:39

ups birth is the first fifteen

28:41

seconds and appears in. there have

28:43

been a I blog posts of

28:45

this kind of real I did

28:47

where I'm zooming through time and

28:49

I'm I'm I'm saying I give

28:51

me this site. dynamic fast moving

28:53

time lapse from lights volcanic ass

28:55

going underwater and then we emerge

28:57

and to like ancient civilizations and

28:59

we're zoom in through like the

29:01

seventeen hundreds, eighteen hundreds and then

29:03

until like. Modern day time. Borrowing all

29:06

the stuff at it and it gave

29:08

me some outlook. I give a shout

29:10

and separate selloum. It was moving the

29:13

camera in a way that was never

29:15

possible with like old film technology and

29:17

it was like making edits with in

29:19

the clip so isn't it? Almost had

29:22

it's own sense of peace in and

29:24

editing and it. Sat. Really

29:26

made me think out and once you

29:29

kind of throw a lot like the

29:31

kitchen sink at the saying and you

29:33

get this really experimental affect, you can

29:35

start to experiment and ways ah, that

29:38

we've never experimented with for And so

29:40

that that really got me excited was

29:42

specifically that and a hallucinatory aspects. May.

29:45

Costs to just walk us through the basic

29:47

steps of the process of making a film

29:50

using a tool like sore us like what

29:52

prompts did you use for this film like

29:54

how long did take you to put it

29:56

all together will and just walk us through

29:58

the prime. the thought of it. So.

30:01

There's a website that you go to

30:04

and there's a tax field and translate

30:06

you know what you're used to, prompting

30:08

with other generative A I tools. And.

30:11

Then it gets sort of translated interpreted

30:13

through chassis be t So it's like

30:15

okay you want best and then it

30:18

it gives you something like that and

30:20

then you can edit the chassis be

30:22

T response bites. The. Process

30:24

of using Saura. I

30:27

feel like is akin to. Trying.

30:30

To tell a story to a

30:32

toddler with superpowers? What he means

30:34

for hits It feels a little

30:36

bit like. This. Naive

30:39

and city with black

30:42

magic superpowers, I

30:44

want to just a route this conversation in the actual

30:46

video that you pretty swiss are are one of the

30:48

videos the producers are as I think we should just

30:50

like watch it together and I will kind of describe

30:52

what we're seeing and then we're gonna ask you some

30:55

questions about it again. It's very chaotic

30:57

and. Can. Addict and dynamic and

30:59

may cause motion sickness baths as I was

31:01

kind of better than nothing to have to

31:04

sign a waiver before watching the video. The

31:06

as as. The

31:15

video that we're looking at right

31:17

now called the Golden Records and

31:20

for people who who are watching

31:22

this on video is basically showing

31:24

a a record like of bio

31:26

record made of gold that is

31:28

sort of hurtling through space. Yeah

31:30

I'm getting a little dizzy. Looks

31:33

like there's a sort of like zooming like

31:36

were zooming through space encountering all these like

31:38

golden orb. So yeah but the kind of

31:40

has tear was to see how how dynamic

31:42

can I make these cameras, How cinematic can

31:44

I. Create. Ah, and a

31:46

static that sales may be different

31:49

than when I had been seen.

31:55

Cool. So that's that's a a clip about

31:57

a minute long. This is not a full.

32:00

Your film but you'd You did make

32:02

this almost entirely with sore us. What

32:05

was The idea? Their. Yeah. So

32:07

I had been fascinated by this.

32:10

Project. Has by Carl

32:12

Sagan and Nasa off.

32:14

Like in Nineteen Seventy Six and

32:17

Seventy Seven where they essentially made

32:19

like a time capsule of as

32:21

humanity. Up until that point they

32:24

collected sounds from my bubbling my

32:26

dad to like human speech and

32:28

then they collected a bunch of

32:31

songs are from around the world

32:33

including like Johnny Be Good is

32:35

on the record and then they

32:38

included an image is into a

32:40

golden record and splash out to

32:43

to and space and hope. That

32:45

maybe Aliens Sunday was literally it

32:47

was. It was a message sent.

32:49

Aliens. In. A We talked about

32:51

sending episodes of Hard Fork out into

32:54

space as of his other alien civilizations.

32:57

Assists the I Do Not Greenlight

32:59

podcasts on your system and. To.

33:05

Ask some questions about the creative process

33:07

your sucks. So many prompts did you

33:09

use to make this. One. Minute

33:11

movie. Yeah. I

33:14

probably. Size.

33:17

But. There's like variations of that, right? So

33:20

when I first got my hands on

33:22

Saura, I was like, how do I.

33:24

Break. This thing harrowing and stick it

33:27

from this like very ai looking

33:29

video ascetic. This kind of slow

33:31

moving camera moves the things that

33:33

feel lights just three, the animation

33:35

or stock footage and so like

33:37

any delays move the camera and

33:39

even if it causes motion sickness

33:41

that was part of the task

33:43

was to see like how crazy

33:45

can can this gets, how chaotic

33:47

can it be and. Just

33:49

for the sake of comparison, how long would

33:52

it have taken you to make something like

33:54

the gold a record using conventional film tools

33:56

and then Salander take you using Saura. Higher.

33:58

I would say with. The how dynamic

34:01

the camera is, how maybe complex

34:03

the renders are, with, you know,

34:05

the materials been used, how many

34:08

shots they are. I'd

34:10

say this would take a a

34:12

a few months to make. I.

34:15

Did. The Golden Record. Maybe.

34:17

In. Two. Or three

34:19

days. Wow. Yeah, suits

34:21

time, France. Did get

34:23

open A I put any restrictions on Saura

34:25

when you were using it Like did they

34:27

tell you you you can't make this can

34:29

a video or you gotta stay away from

34:31

this kind of prompts? Did they give you

34:33

any guidance? or did they just sort of

34:35

give you access this tool and and say

34:37

go nuts. They. Specifically wanted

34:40

to be like as hands off as

34:42

possible but it was obviously an hour.

34:44

Like know, like nudity, know, extreme, yeah,

34:46

gore or that kind of staff. so

34:48

they're go. All of Kevin's ideas for

34:50

making to see was sore at the

34:52

i know it's on your eyes to

34:54

different. Era your

34:56

deflating is how hot pot as you as

34:58

you reflect on the experience as a making

35:00

their the sword Psalms that you have made

35:03

with swore I would you say that on

35:05

the whole the process felt easier than you

35:07

expected, more difficult than you expect a. Light

35:09

like well what we're we're your expectations for what

35:11

the same was gonna be like and and where

35:13

did the the result fall? I.

35:15

Actually had somewhat like tempered expectations.

35:18

I was just like this is

35:20

you know a cool tech demo

35:22

that I saw from like our

35:25

a massive company with tons of

35:27

compute power. But is this. A

35:30

clickable: The filmmaking and.

35:33

After ten of breaking and loosening

35:35

up the camera I was like

35:37

okay this can give us some.

35:40

Like experiments, you know,

35:42

wilde bold weird things

35:44

that that may be

35:46

difficult to achieve with

35:48

other tools. And sasser

35:50

when I times. Crafts.

35:53

Or a series of of words

35:55

is basically kind of like Alchemy

35:57

Woods with words. Then I was

35:59

like okay, this can allow for

36:02

the shot types that an idea

36:04

is that maybe just killed in

36:06

the process of so making sweet

36:08

what are some of the secret

36:10

words you found Success Let's see.

36:13

Ah, Thirty five millimeter Fuji film

36:15

stock, Twenty four millimeter, an Amorphous

36:17

Lands analog, warm vintage tone, chromatic

36:19

aberration, whole A since ah, things

36:22

that are like I guess words

36:24

to describe literal sounds and to

36:26

see what's in that the training

36:28

data Basically. That's. Interesting. So it's

36:31

basically like your ears are giving it

36:33

the instructions that you might otherwise give to

36:35

like a cinematographer Someone who's yeah, say

36:37

like what tailored suit on film Ram

36:39

Regulators has. Ah, D P I

36:41

give me a lesson. Chromatic Aberration Like you know

36:43

they're just gonna be like but I had a

36:45

bad case of police and chromatic aberration was but

36:47

I went to the doctor and a clear night

36:49

out. The sad. Part I

36:51

I just have a very basic nuts and bolts question

36:54

which is like you type in a prompt in the

36:56

Saura. You fill it with

36:58

all these magic words he hit, enter how

37:00

long does it actually takes to get the

37:02

video back as it insert now, but? Faster.

37:05

Then you would think it is how long are

37:08

we talking here I heard from someone else it

37:10

it's like like ten or fifteen minutes usually between

37:12

when you put in the prompter when it goes

37:14

back to videos that consistent with your experience. Roughly.

37:17

I just depends on the third, the

37:19

settings. or are you at seven, twenty,

37:21

pete and eighty? It's ah slight the

37:24

saturation. but to do a really. Simple.

37:27

You know, like shot of just

37:29

a ball on the ground that's

37:31

fifteen seconds long? Will

37:34

take just as much rendering time as

37:36

doing and like a crazy it's Golden

37:38

Records, Turtle, Interspace and Exploding and all

37:40

this stuff so that's actually really fascinating

37:42

is what it does. surrender time so

37:44

as having use this for awhile now

37:46

are you thinking about this like oh

37:48

yeah This is definitely a tool that

37:50

I want in my arsenal going forward

37:52

as I continue to make films like

37:54

and a sort of see a lot

37:56

of applications for this sort of more

37:58

in the i could take. It or leave it

38:00

out. I. Would

38:02

definitely. Keep. Using

38:04

this for this is supplements all

38:07

this is not replacing by any

38:09

means and this is like a

38:11

much better alternatives to stock footage

38:13

be role and yeah again allows

38:16

you to discover pass you may

38:18

be wouldn't have gone down by

38:20

yes I I still think do

38:22

so what control and you want

38:25

nuance and you want pay seen

38:27

you're gonna have to use the

38:29

regular tools and I. I

38:32

still find it to be more gratifying

38:34

to do things the traditional way, but.

38:36

Damn. It gives you some really crazy stuff

38:39

that. Is. Outside of the Box I think

38:41

the outside of the box staff is the most

38:43

exciting and. When the.

38:46

Demos. Of sore I went online

38:48

and people actually started to see some

38:50

of the footage that was emerging from

38:52

the system. There were a lot of

38:55

people. Especially in Hollywood who had

38:57

sort of a panic about it and Tyler

38:59

Perry that the famous director said in an

39:01

interview with the Hollywood Reporter that he was

39:03

basically bowled over by some of this footage

39:06

and that he was actually planning to put

39:08

on hold and at a plant expansion of

39:10

his studio because he was just like i

39:12

don't know what what I need right now

39:14

what he'd go. If I can just sit

39:17

in my office and creates amazing foot is

39:19

using this ai tool, you know why do

39:21

I need to go through that? It's the

39:23

no hassle of building at an expensive studio,

39:26

so. Do you think those people who

39:28

saw this and freaked out are overreacting? Is it

39:30

the case that Decks are? The closer you get

39:32

to this technology, the less impressive it is. Or

39:34

to what do you make of some of the

39:37

responses that have come out about this tool? I.

39:40

Feel like the more. You. Use

39:42

these tools the less afraid you

39:44

are of them because you do

39:46

understand their limitations and you understand

39:48

their place for them. And you

39:50

understand what separates this from. using.

39:52

Other traditional tools be affects

39:55

her in camera or actors.

39:57

I think what Tyler Perry

39:59

is same. The Is. Somewhat.

40:02

Harmful and sending the wrong message to

40:04

people that are at the top at

40:06

the studio level that are the gatekeepers,

40:08

the ones that have the money to

40:10

say hey guys, let's not spend our

40:12

money And as it's incredibly capitalistic way

40:14

of thinking, South it's

40:17

not the in think he's from

40:19

necessarily about the potential of the

40:21

technology to displace labor in, so

40:23

making it's that's enough. Basically this

40:25

is this is served someone. Same.

40:27

Acquire part out loud. Like saying we we might not

40:30

want to spend all this money on humans. I think

40:32

it's both to. I mean, he hadn't. Even

40:34

tested sore at the time. I don't

40:36

know if he has it now, but

40:38

am I think he had the wrong

40:40

interpretation of of sort of been this

40:42

kind of replacing everything? It'll create certain

40:44

efficiencies for sure, but they're all the

40:46

people. Are the people on Twitter that.

40:48

Love. To tweet the line or

40:51

Ip Hollywood I really encourage them

40:53

to go and actually watch a

40:56

movie. By seriously

40:58

don't watch a movie trailer,

41:00

Go watch a real movie

41:02

and see how much nuance

41:04

and detail and micro decisions

41:06

that are made at every

41:08

split second of Asylum. From

41:10

from an actress choice sad,

41:12

the A, Static, and everything

41:14

movies are incredibly complicated. Let.

41:16

Me ask about it at a different

41:18

way in earlier in the upset at

41:20

we are talking about the fact that

41:23

I have for a while I put

41:25

a i generated images into my newsletter

41:27

and my readers ultimately just trainers revolted

41:29

against at like I got a lot

41:31

of feedback to spend like we hate

41:33

this year you're using images that were

41:35

trained are not copyrighted material. Your taken

41:37

away money friends from human illustrators I

41:39

imagined you know that that you you

41:41

might have gotten some some similar feedback

41:43

where you can at least imagine getting

41:45

that's he backstory you think. About

41:47

Those questions. Source:

41:49

At Wealth, can I ask what? what was

41:51

your illustration budget per year for your newsletter?

41:53

I will. So that's the thing I was

41:55

A. and you know, I mean I had

41:58

access to some image libraries like Getty. Images

42:00

you know he in are all those cases

42:02

a a human being was was paid for

42:04

their labor rights to that's what I but

42:06

using but I was not commissioning standalone illustrations

42:08

for for my pieces. Exactly. I

42:10

think that's what people are missing

42:12

is that we are creating content

42:15

now that simply wouldn't have existed

42:17

before. Sure, there can be pretty

42:19

studio heads at the top of

42:21

that, will try to find ways

42:24

to lights at the bottom line

42:26

and increase their margins, but. For

42:29

the most part of people that are

42:31

using these things are making things that

42:33

that just wouldn't have existed. As you

42:35

see musicians and notoriously have zero budgets.

42:37

Sometimes they posts like I and a

42:39

i just Generated image on Instagram and

42:41

then people like our no not you

42:43

use a I to like oh My

42:45

God cancel on subscribes and it's a

42:48

site. But. They wouldn't have

42:50

posted anything that day if they didn't have

42:52

a I am and so it's It's kind

42:54

of like opening up a new channel. and

42:56

I mean yes, there's like sensitivity around. like.

42:58

Black. Box of what's been trained

43:00

on. But reality is we can

43:02

buy clothes. Pandora's Box waiting like.

43:05

Technology. Is relentless and and we

43:07

have to just kind of adapt using these

43:09

things. The way I feel like the narrative

43:11

needs to be kind of steered is that.

43:14

Ninety nine percent of scripts and

43:16

hollywood get rejected and an even

43:19

of the one percent that get

43:21

and bought. Only. About half

43:23

of those go into production and

43:25

so I think this will open

43:27

up the opportunity for people with

43:29

these ambitious and bold ideas to

43:31

resurrect. Project said that when they've

43:33

existed. I'm even going back to

43:35

some music video concepts and I

43:37

pitched in the past that just

43:39

like weren't gonna work for the

43:41

budget. Yes, I

43:44

have seen some backlash pointed

43:46

at you and other filmmakers

43:48

who has been experimenting with

43:50

these tools. physically accusing open

43:52

a i was artist washing

43:54

of your face of a

43:57

using artists to sort of

43:59

test out. Tool to show all

44:01

the cool and creative uses for them

44:03

while actually certain negotiating behind the scenes

44:05

to add to replace a bunch of

44:07

labor or to to use these tools

44:09

that many artists feel have been trained

44:11

on their work or or work of

44:13

their colleagues without permission. So what else

44:16

you could just speak to that they

44:18

this idea of open a I sort

44:20

of using artists and filmmakers to try

44:22

to convince a skeptical public that all

44:24

the stuff is just going to be

44:26

good and can enhance creativity and that

44:28

it's not gonna replace anyone's. Jobs while

44:30

actually having a very different strategy

44:32

behind the scenes. Shore and. I.

44:35

May I think that is a very

44:37

fascinating points and I it's something I

44:39

kind of grapple with all the time

44:41

because I have I again I still

44:43

love to do the traditional way I

44:45

so love to employ people are then

44:48

the other side of me as a

44:50

plane with all this new tech and

44:52

I might am I just some sort

44:54

of pawn in the sights. grades master

44:56

plan as of Agee Eyes but it's

44:58

I've What is that? The opposite of

45:00

this as you don't want artists involved

45:02

in the research process. I feel like

45:04

including artists if you're developing. Things that

45:06

are that as visual technology including artist

45:08

in the process is is critical because

45:10

otherwise you're just kind of in. This

45:12

does Bubbles, Am and and young really

45:15

understand like what the purposes of your

45:17

research. A. What one question that

45:19

comes to mind for me Paul is what are you

45:21

working on next with this thing? Can you give us

45:23

a preview of what else you think you can do

45:25

with us Aura? Yeah I

45:27

mean. So. I will say

45:29

everything has to be kind of run

45:31

through open a I in order to

45:33

make it to the public. They are

45:35

being very kind of selective with that

45:38

they so they don't I can inundate

45:40

people the been careful with how much

45:42

as is released but I have my

45:44

brain has been spiraling. I've been. Working.

45:47

On. A short song

45:49

I'm I'm also I'm working on a music

45:51

video and on of that's a breaking numbers

45:53

in bringing it up as broken as has

45:55

hats so that that will add that can

45:58

say who are when or what bad. Well

46:00

let's just say Beyond Say does have a new

46:03

record out in. a lot of people are listening

46:05

to us as a specific answer is yes. That

46:08

and then the schools and record projects

46:10

and Sleaze is bigger. But I'm also

46:13

I'm I'm still exploring other routes and

46:15

I don't I don't see sore as

46:17

as oh, I'm only going to focus

46:19

on this tool to get everything out

46:21

of my head. It's just a at

46:23

the supplemental saying, but it's it's been

46:25

very liberating. I'll say that. I.

46:28

Bought we Gotta Run and

46:30

so much larger that I

46:33

really appreciated cynicism. Lox. Debate

46:40

on something sedated. This

46:54

podcast is supported by Americans United

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More about a use work at

47:25

a You.or access and whitey. Kiss.

47:29

You know we love a caper on

47:31

this show. Off we Love a Keeper

47:33

On Saturday I have when I believe

47:36

is the biggest tech caper of at

47:38

least the past year. Okay well then

47:40

let's hear about it. And I want

47:42

to preface this caper by saying that

47:44

this is going to involve a lot

47:46

of terms from the Linux and open

47:48

source software development and various databases. And

47:50

and I need you not to fall

47:52

asleep because the payoff is gonna be

47:54

worth and will there be a quiz

47:56

at the at the typical V? Oh

47:58

yes. So this is. A A

48:00

very interesting and strange story that came

48:02

out of the world of cyber Security

48:05

over the past week. and it involves

48:07

a thirty eight year old software engineer

48:09

named Andreas Frames good for of the

48:12

pod the effort Griffin Health of I

48:14

did. He was in San Francisco, he

48:16

works at Microsoft and he stumbled into

48:19

what may be the biggest attempted cyber

48:21

attack in history, Which it's crazy that

48:23

sort of just one person could stumble

48:26

into something as big as the says

48:28

yes, I've been totally obsessed with. The

48:30

stories are basically I. I think we

48:33

should just explain off the bat that

48:35

the internet is a very sort of

48:37

rickety contracts. I think most people don't

48:40

understand this unless you talk to people

48:42

who are engineers or work and cyber

48:44

security. or sort of develop the set

48:47

of building blocks and which the entire

48:49

Internet rests. It's weirdly precarious that it

48:51

works. I had an hour. Honestly, someone's

48:54

miraculous right? because imparts so much of

48:56

the internet, the technology reliance depends on

48:58

these tiny little open. Source projects that

49:01

might be maintained by for example,

49:03

one person gets the other. There's

49:05

a famous Xkcd comic where you

49:07

have kind of like a a

49:09

a a vast must or that

49:11

is sort of resting on one

49:13

little sin Like Rob and the

49:15

elaborate machine is labeled all modern

49:17

digital infrastructure and the little peg

49:19

that it's resting on is labeled

49:21

a project some random person in

49:23

Nebraska has been sank with we

49:25

maintaining since Two thousand and three

49:27

at this story is the literal

49:29

instantiation of. That cartoon because of it

49:31

as a sort of our society bad

49:33

as yes, this is the tiny peg

49:35

that is holding up the giant machine

49:37

called the Internet. And how one guy

49:40

Andreas Freud's I discovered basically by accident

49:42

a plot to kind of mess with

49:44

the entire internet as we know it

49:46

all right. So how are we stumble

49:48

across as Plucked Oven so he works

49:50

in Microsoft. He develops this piece of

49:52

open source database software called Post Dress

49:54

Up. The details aren't important but this

49:56

a big database. Lots of companies use

49:59

it. It's open. The Worth Hundreds is

50:01

one of the people who maintains it's

50:03

database. As part of his work, he

50:05

does a bunch of tests to make

50:07

sure that various pieces of this software

50:09

are running correctly. A few weeks ago

50:11

he's doing some tests and he says

50:13

noticing some weird error messages and at

50:15

the time you know he's flying back

50:17

from Germany, was visiting his parents his

50:20

German and he's sorted, set, lagged. He

50:22

thinks okay, maybe this is not important,

50:24

I'm just gonna collect ignore these error

50:26

messages then he gets home to San

50:28

Francisco. He starts running some

50:30

more pasts and he says noticing

50:32

some other weird error. Some anomalies.

50:34

Some anomalies. Yes, he notices For

50:37

example of that, this process called

50:39

Ss H. It's running sort of

50:41

slower than possible by a little

50:43

bit is using more processing power

50:45

than I usually would. It's causing

50:47

some memory errors that usually aren't

50:49

there. Now can we say slowdown

50:52

isn't slowing down by like thirty

50:54

seconds? None of these delays, they

50:56

are. They are tiny. It's like

50:58

measured in milliseconds. But your Andreas

51:00

is a very detail oriented guy. He's

51:02

been working on this particular piece of

51:05

software for a long time. Any kind

51:07

of knows what it's all supposed to

51:09

look like and so he started noticing.

51:11

Like a little lag there a little

51:13

more Cp use uses. Here's something is

51:15

going wrong. Hey, Spidey sense starts to

51:18

tangle exactly. So he basically starts digging

51:20

in and investigating. And he traces the

51:22

issue to the set of data compression

51:24

tools called X the Utes Hills. I

51:26

wondered if it might be an axial

51:29

tilt. Member of a specific it gets So

51:31

you're basically the details of what the Sig

51:33

is are not important but it of I'd

51:35

try it would just that are to me

51:37

it's a set of data compression tools that

51:39

is all I now okay sort of like

51:41

the of the premise of the old Silicon

51:43

Valley Tv so exact I but x you

51:46

tilt is used by Linux, the open source

51:48

operating system and another piece of information that

51:50

you need to know at the story that

51:52

linux is probably the most important piece of

51:54

software and the were linux is everywhere. Yes

51:56

so Linux is used by the vast majority

51:58

of. The world. Data Centers servers

52:01

like every major really important computer

52:03

in the world runs on Linux.

52:05

Or there's a computer talking to

52:07

another computer somewhere Linux is involved.

52:09

Yes, Yeah. So this little tiny

52:11

software package exit you tills is

52:13

a very small piece of a

52:15

very important piece of software. So.

52:18

Audrey starts looking into these weird delays

52:20

and and these weird anomalies and he

52:22

eventually starts looking at the source code

52:24

for accede you tells and he discover

52:26

something that blows his mind with as

52:28

he finds a backdoor. Now a backdoor

52:30

I know you're gonna make a joke

52:32

about. I'm not going to make his

52:34

else about best or you're passing up

52:36

jokes about backdoors today. Something is wrong.

52:38

Are you okay Timothy Mcveigh This is

52:40

plenty of the keep say but I'm

52:42

not going to make a joke of

52:45

it as a fastball over the plate

52:47

of my friends. Is. That

52:50

of so it is basically a back

52:52

is a piece of malicious code that

52:55

is inserted into a piece of software

52:57

that allows and it's hacker to to

52:59

basically remotely access or control that are

53:02

sort of slip in some code to

53:04

they road space we do something malicious

53:06

it's it's kind of a seats to

53:09

unlock a piece of software of with

53:11

the intent to mess with it in

53:13

some way goddess So. Andreas.

53:16

Is not a cyber security engineer, he's

53:18

just a guy who maintains a database

53:20

and but he finds this evidence that.

53:23

X you till this tiny piece of

53:25

linux has been compromised that someone has

53:28

intentionally gone and and placed a backdoor

53:30

their that that if you are that

53:32

person you can then go in and

53:34

you can basically tamper with any computer

53:36

that is running Ssh on linux which

53:38

is to say the vast majority of

53:40

the important computers on earth which like

53:42

I'm just imagining being here Myths and

53:45

like you've noticed these this like series

53:47

of small anomalies as you have that

53:49

feeling that something is amiss yes but

53:51

I bet that even in his wildest

53:53

imagination. He did not imagine that.

53:55

He vowed a very sophisticated backdoor

53:57

know. So I talked to Andreas.

54:00

The his discovery, he's or walked me

54:02

through the whole thing any says it.

54:04

At first he was sort of like

54:06

skeptical of his own findings. He said

54:08

it's seltzer real. He said there were

54:10

moments where I was like I must

54:12

have just had a bad night of

54:14

sleep and heads and fever dreams. Basically,

54:16

this is not the kind of thing

54:18

that you find in a widely scrutinized

54:20

piece of software like Linux. And so

54:22

Andreas. He looks at this, he says

54:24

man and or know this to sounds

54:26

like too big to be true. And

54:28

how could something like this. Agnew to

54:30

get approved and make it's way into

54:32

the the release version of linux but

54:34

he keeps digging, he keeps finding new

54:36

evidence and then last Friday he basically

54:38

rights up what he found and sends

54:41

it to this group of open source

54:43

software developers and he makes a basically

54:45

says all these errors that I've been

54:47

seeing all these anomalies in this me

54:49

know in In is very obscure software

54:51

packages. It's all because this

54:53

thing has been back toward. Someone is

54:55

here messing with this release and they

54:57

are intending to use this to to

55:00

basically break into a bunch of computers

55:02

and do whatever they want. So earrings

55:04

the Alarm of Hearings. The alarm. And

55:07

immediately the entire cyber security world meltdowns.

55:09

I talked to one researcher Alex Stamos

55:11

i know you know he's a former

55:13

as Si A at Facebook is now

55:15

are involved in some the called Sentinel

55:17

One which is a cyber security research

55:20

firm and he told me this could

55:22

have been the most widespread and effective

55:24

backdoor ever planted in any software products.

55:26

while and basically you know what people

55:28

I talked to said his. Look, if

55:30

you have this back door if you

55:32

have this master teeth that lets you

55:34

get into any linux computer that is.

55:37

Running as as a it's is

55:39

very ubiquitous software package, you essentially

55:41

have a way to get into

55:43

hundreds of millions of computers around

55:45

the world. Once in their, you

55:47

can steal private information, you can

55:49

intercept encrypted traffic, you can plant

55:51

malware, you can cause major disruptions

55:53

to like big pieces of infrastructure,

55:56

and critically, you can do all

55:58

of this without being caught. Because

56:00

part of what. Andreas. Discovers as

56:02

is investigating this back door is that

56:05

whoever planted it there has taken

56:07

steps to ensure that is very hard

56:09

to detect. And you know

56:11

basically this would have worked if not

56:13

for Andreas and his very eagle eyed

56:15

detail oriented like obsessive approach to add

56:18

trying to figure out what the heck

56:20

was going on with these error message

56:22

This is why nerds are so important

56:24

to the economy and to celebrate a

56:27

bit. three celebrated are such as if

56:29

people that are like this process is

56:31

running one second to slow cancel my

56:33

afternoon, we elevate you totally. So this

56:36

discovery i think it's safe to say

56:38

it is is a huge shock waves.

56:40

Through the world of cyber security because

56:42

you know this thing was caught before

56:45

it could do any real damage. It

56:47

had not made it into the sort

56:49

of widely used versions of Linux that

56:52

all these servers run on, but it

56:54

would have any, Would have been a

56:56

potentially disastrous I'm now that are. Andreas

56:58

has kind of become dislike nerd hero.

57:01

All kinds of people are are are

57:03

praising him. Satya Nadella his served as

57:05

the Chief executive Microsoft his bosses boss's

57:07

boss as a praise him for his

57:10

curiosity and craftsmanship. Are there was

57:12

a popular are post the went around

57:14

calling Andreas be Silverback gorilla of nerds

57:16

and people are basically comparing him to

57:19

the little Peg in that a comic

57:21

than all of modern capitalism rests on.

57:23

Okay let's get the who did this

57:26

cousin to. That's what everybody wants to

57:28

know right? Who's responsible for this backdoor?

57:30

Those was as bad or bad it.

57:32

So here's what we now so far

57:35

according to some researchers I talked to

57:37

this is so elaborate. this plot was

57:39

was so sophisticated. That it couldn't

57:41

have to spend like a random group of

57:44

hackers. This had to have been like a

57:46

nice and state like a Russia or China

57:48

or and North Korea someone with access to

57:50

vast resources and very skilled teams of hackers.

57:52

Web island. I'm interested in that cabin because

57:54

as far as I can tell, the main

57:57

thing that separates this attack from many of

57:59

the other attack. That U C all a

58:01

time is just how much time they invested.

58:03

Employee lot right suits us to talk to

58:05

us about all the time involve. He has

58:07

a one of the cool things about open

58:09

source software that you can actually go back

58:11

in like see all of the changes and

58:13

who was requesting them and and what they

58:15

actually met in terms of what ended up

58:17

in the codes and so researchers have been

58:19

going back and from trying to forensically look

58:21

at all the evidence trying to set of

58:23

see how this happened and they found a

58:25

really interesting story buried in some of the

58:27

details of this software. So

58:30

back and Twenty Twenty One there's a

58:32

user who creates a get have account

58:34

and starts contributing to various open source

58:36

projects. This user uses the name Xia

58:39

Tan for various reasons. Researchers actually don't

58:41

think that's a real name, it's probably

58:43

a pseudonym. sort of. Smarter soon. Amid

58:45

the what I would have picked which

58:47

would have been backdoor wizard this s

58:50

a G, A Tan or whoever it

58:52

is they start suggesting sort of the

58:54

teams is to access you tills starting

58:56

back in Twenty Twenty Two. And

58:59

this is the ways that Open Source development

59:01

and a Works is like. People proposed, been

59:03

to changes and and and indies special our

59:05

inner tubes developers called maintain or were sort

59:07

of in charge of a projects. They look

59:09

at the proposed changes they serve, test them,

59:11

mixer, they work, see what affects they have

59:13

on performance and then if they're good they

59:15

approve them in that kind of gets like

59:17

merge into the main coed but the basic

59:19

ideas that everyone who participates is essentially a

59:21

good samaritan. right there somebody comes along and

59:23

says i use the software I noticed this

59:25

thing could be better. What am I right?

59:27

A little co depicts it's also. Minutes you

59:29

and if you like it's you can share

59:31

with everyone. Yes, and many of these projects

59:33

only have one or a handful of maintain

59:35

as a test them because these are not

59:37

like these are not like Sas moving software

59:39

objects. Rothys are not things that are being

59:41

constantly refined and redevelop. He's a specific. This

59:44

is what infrastructure that yeah like is what

59:46

you you built the A You have a

59:48

plumbing ducts for the internet and it's just

59:50

gonna sit there mostly and people are going

59:52

to build on it and use it for

59:54

stuff that they're building. but you actually don't

59:56

need much more than one person to kind

59:58

of keep tabs. On this project right? Mostly

1:00:00

done but software is never totally

1:00:02

done exactly So this person's yeah

1:00:04

Hannity. This group of people using

1:00:06

this names yet hands start kind

1:00:09

of proposing changes and then they

1:00:11

start of gradually serve social Engineering.

1:00:13

The entire team that's involved in

1:00:15

maintain this project which again is

1:00:17

mostly comes down to one person,

1:00:19

one maintain or has been doing

1:00:21

this for many years. Sergio.

1:00:23

Ten starts contributing be sort of

1:00:25

minor proposed changes to X You

1:00:27

Tells Back and Twenty Twenty Two

1:00:30

and then something interesting happens. which

1:00:32

is that, See a tan? Whoever

1:00:34

it is, whatever national the hacking

1:00:36

team it might have bands they

1:00:38

start trying to is basically take

1:00:40

over control of X The You

1:00:42

tells. And they do this by

1:00:44

essentially seizing on the fact that

1:00:46

the person who maintains this software

1:00:48

project is getting kind of tired

1:00:50

of doing it the the third

1:00:52

Don't wanna do this anymore. It's sort

1:00:54

of sounds like and so it's just Han,

1:00:56

whoever it is test sticks their hand up

1:00:58

and says well what if I was the

1:01:00

main tanner and I would if I could

1:01:03

like solve this problem for you by taking

1:01:05

over this very thankless task of maintain this

1:01:07

tiny little software like think that problem off

1:01:09

your hands. So over the course of a

1:01:11

couple of years Jets hand builds frost with

1:01:13

the other people who are involved in contributing

1:01:15

to this software tool and as and eventually

1:01:18

gets named a maintain her of this project

1:01:20

and so he is able to kind of

1:01:22

do the final approval for. This proposed

1:01:24

code seems that would insert this hidden

1:01:26

back door into the software project, effectively

1:01:29

becoming a double agent like something

1:01:31

you would read out of a novel

1:01:33

by a lake. Or it's while

1:01:35

it's a it's like honestly v be

1:01:37

trade craft. The kind of spycraft involved

1:01:40

in this is a very sophisticated

1:01:42

operation. It involves not it's a technical

1:01:44

piece of of of hacking but also

1:01:46

have a social peace where you're

1:01:48

kind of winning over the small team

1:01:51

of very harried, very under appreciated

1:01:53

developers. You're volunteering. To help them,

1:01:55

you're kind of establishing your credibility

1:01:57

in this very tiny community. And

1:01:59

eventually years. Using their credibility to install

1:02:01

a backdoor that will let whoever it is

1:02:03

have access to hundreds of millions of computers

1:02:05

and do whatever they want with them. A

1:02:08

wild story It as and now I know

1:02:10

that we don't know truly anything about the

1:02:12

real identity of G A Damn. But I'll

1:02:14

tell you, I like thinking of G A

1:02:17

Tan as as a deadly woman assassin Carmen

1:02:19

Santiago back of the Ideal Computer Games yeah,

1:02:21

sort of yo international criminal and In In

1:02:23

your is very elusive. G at hand is

1:02:26

the new Carmen Santiago. That's true, you know,

1:02:28

and I think we should devote. Many episodes

1:02:30

of podcast trying to track down to his hand at

1:02:32

the end of every episode where they were the world

1:02:35

as the attack and we're going to keep saying it's

1:02:37

a we find out at night part of that show

1:02:39

was the the do It Rock capella remember that yes

1:02:41

it was one of the only are capella theme songs

1:02:43

river Heads for a show and it was so successful

1:02:46

that they should up accessory so. I.

1:02:48

Think there are lot of things to say

1:02:50

about this story, but one of the search

1:02:52

interesting side discussions that I've seen and come

1:02:54

out of this. You know there's this whole

1:02:56

group of people in Silicon Valley who believe

1:02:59

that a I should all be open source

1:03:01

and that the reason that you would want

1:03:03

something like you know as an Ai language

1:03:05

mile to be open source is because then

1:03:07

you'll actually be safer because then you'll have

1:03:09

not just one company kind of trying to

1:03:11

keep the bad guys that you'll have this

1:03:14

kind of distributed army of volunteers who are

1:03:16

constantly sir looking through things, poking around in.

1:03:18

The source code. It's happened to the Global

1:03:20

Nerd Hives, exactly. And that's so how are

1:03:22

you get things like Linux, which are the

1:03:24

result of thousands of contributors working on their

1:03:27

little pieces of this thing? Eventually it all

1:03:29

comes out in it's pretty secure for the

1:03:31

most parts of and so that is One

1:03:33

thing that those people are now saying is

1:03:35

this episode with X the the X the

1:03:38

Back door and proved that all software needs

1:03:40

to be open source. When a mega that

1:03:42

I mean look at all. So all software

1:03:44

does not need to be open source. It's

1:03:46

perfectly fine to haven't from a. Private companies

1:03:48

making their own software. But I think to

1:03:51

the degree that a piece of software is

1:03:53

traditional to how the internet works out, there

1:03:55

is a really great case for making it

1:03:57

open source. Yes, I am saying for to

1:03:59

under is not just for saving us all

1:04:01

from doom, but also for forcing me to

1:04:03

learn about Linux development and open source repositories

1:04:06

and maintain. Or that I guess I'm just

1:04:08

struggling with one more question Kevin which as

1:04:10

we enter this been oh brave new world

1:04:12

where there are a lot of G attempts

1:04:14

out there. What are you doing to protect

1:04:16

your backdoor? And

1:04:19

that that's all we have this week's on

1:04:22

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Before we go, we continue to be really

1:05:17

interested in how young people are using technology

1:05:19

and we've been hearing stories about snapshot causing

1:05:21

drama in middle schools and high schools and

1:05:23

we want to see or about it. Has

1:05:26

snapshots roiled your school or your kids' school?

1:05:28

In some ways, what was the snaps at

1:05:30

incident where you lived? Let us know. Email

1:05:32

us at Hard Fork and I would have

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zoc up the mess years a better. Or

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works for it by Resort Town

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and Whitney. Chance of Winning Edited

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by and points of Accept My

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Caitlin Love Studies show was engineered

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Towel or Audience editor is no

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globally. Video. Production by Ryan

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Manning and Don't Ferguson has you either.

1:06:00

I got our youtube channel the You

1:06:02

tube.com/for for special thanks to Polish Human

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We wings him a prestige and

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different as always. You can email us

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at third, fourth and. You

1:06:12

know, Some

1:06:35

for quick break to Taco Bell Mcdonalds

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we got in big lies. Did your

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taste buds ready for Mcdonalds breakfast bagel

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1:06:59

participating Mcdonalds. Must have been to awards.