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The value of investments may fall as well as rise, and

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you may not get back the amount originally invested. Welcome

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to the New York Times Popcast. You

0:43

are language too vast for any training

0:45

model to grasp of music, news, and

0:48

criticism. I'm your host, John Karamanica. I

1:25

know for years you've been listening

1:27

to podcasts and thinking, these guys

1:29

need a theme song. Why

1:31

don't they have theme songs? Well, what

1:34

did I spend the last few days doing while playing

1:37

around with Suno and UDO, which

1:39

are two of the leading music

1:41

AI interfaces to approximate

1:44

what a popcast theme song might

1:46

sound like. I

1:48

put some prompts in and came up

1:50

with a bunch of different options, which I'm

1:52

going to be sprinkling through the show

1:55

this week, which is completely

1:58

devoted to contemporary. uses

2:00

of artificial intelligence in music, we

2:02

are going to be talking with

2:05

Rachel Metz, who covers artificial intelligence

2:07

more broadly at Bloomberg and Kristin

2:09

Robinson, who covers the music business,

2:12

including how the record industry is

2:14

trying to use AI for Billboard.

2:17

What you were hearing at the beginning of the show,

2:20

you were hearing, there's no name,

2:22

it was made with Suno. It's

2:24

the first track that

2:27

was generated with the prompt

2:30

of asking for a pop cast theme song

2:32

that sounded like 90s Midwest

2:35

emo. And I'm not

2:37

going to lie, they definitely got

2:39

that parts thing down. They definitely

2:41

got that sort of dry male

2:43

vocal thing down. It's a little

2:46

unsettling, but also kind of a

2:48

joyful experience. As I said,

2:50

throughout the show, we're going to be playing a

2:52

few other things that I'll be throwing to. But

2:55

for now, let's get into the

2:57

conversation. Rachel Metz is

2:59

here, Kristin Robinson is here.

3:01

Welcome to podcast. Thank you.

3:03

Everybody coming in virtually, but

3:05

hopefully authentically not artificially today,

3:07

fingers crossed. So I know

3:10

I've been keeping tabs on what's been happening with

3:14

AI music making intermittently

3:16

for the past, let's say six to 12

3:18

months. But both of you, this is a

3:20

very, very key part of your beats. Rachel,

3:23

you cover AI more broadly, music being one

3:25

segment of that. Kristin, you cover the music

3:27

business more broadly, AI being one segment of

3:29

that. And one of the reasons, the reason

3:32

I wanted to have both of you on

3:34

is I think you're approaching it through different

3:36

lenses, the same subject matter through different lenses

3:38

through your work. So I

3:41

thought it'd be interesting overlap and intersection

3:43

of perspectives. Can

3:45

we start with a thing that

3:47

happened recently that Felt

3:50

itchy to me? And Maybe we can start

3:52

with this as a fact as an also

3:54

an indicator of what's to come and maybe

3:56

then rewind and say, how do we get

3:59

to it? Really Travis. Really

4:01

Travis is and what has been

4:03

for many years. one of my

4:05

favorite country singers. Suffered a stroke

4:07

in twenty thirteen I believe and

4:10

and no longer Kim sang and

4:12

as a Randy Travis fans on

4:14

the grew up on the late

4:16

eighties early nineties hits emails of

4:18

a big loss but also I

4:21

currently music for a living. I

4:23

accept that not everything goldstein last

4:25

and that's okay as an older

4:27

son. Negative press release advertising a

4:29

new. Randy Travis songs and like

4:32

instantly I feel like the muscles

4:34

and my my max the top.

4:36

My soldiers defend a seal, the

4:38

discomforts and so what they've done.

4:40

This is a song called where

4:42

That came from and so let's

4:44

listen to Little Some the. Law.

4:56

So if you are fan or

4:58

any Travis, you're obviously you'll recognize

5:00

the voice of feals. mostly like

5:02

a rainy Travis voice. The inflections

5:04

feel like a good approximation of

5:06

Randy Travis, since, like some. What?

5:09

You're Actually Feeling isn't a i modeled

5:11

streamed on vocal stamps of about forty

5:13

Randy Travis songs overlaid on top of

5:16

a guide demo vocal sung by a

5:18

difference singer theoretically in the mood or

5:20

in service. The song itself is a

5:22

demo The the Asshole song was written

5:24

for any thrive as many years ago,

5:26

so it's not totally out of the

5:29

blue where they got these lyrics from,

5:31

or the idea from. But.

5:33

This is likely be the first

5:35

of what I imagine to be

5:37

many posthumous or posthumous asked recordings

5:39

for artist who know I can

5:42

make original recordings when when y'all

5:44

encountered this. Just. As a

5:46

fact did this seems. This.

5:48

Is normal? This is where it's going.

5:50

Or did anything about this see a

5:52

little bit Etsy. Maybe Rachel would start

5:54

with you and then we'll go first

5:56

and. For. Me is the first thing

5:58

I think is. I

6:00

have some questions about consent. Whose idea

6:02

was this? Did Randy

6:05

want to do this? How do we know that

6:07

he wants to do this? If

6:10

somebody has already died and they're a

6:12

state, they can make those decisions then.

6:15

And that seems totally fair to me. But if someone

6:17

is still alive, I think then it brings up

6:19

some really tricky questions. But aside from what does

6:21

it sound like and do we enjoy how it

6:23

sounds or is it creeping us out? And

6:27

I think the consent question is really interesting. There's

6:29

a CBS morning show or

6:31

Sunday morning show segment about this. And

6:33

he's in these rooms, but so

6:36

are cameras. I don't know who

6:38

was in those rooms when no cameras were

6:40

there. And also he can speak a little

6:42

bit, but not extensively. We

6:44

don't genuinely have a way

6:47

of knowing. One of the actual things that comes

6:49

up in the CBS Sunday morning segment, the

6:51

interviewer asks, he's there with Randy, he's there

6:54

with his wife. In

6:56

essence, you have thoughts, but you are

6:58

not able to express them. And

7:00

Randy sort of nods and said, yes. Do

7:03

we know how robust that process? We just

7:05

don't know. And I think the consent thing is

7:07

real. I have no idea if Randy Travis

7:09

wants this to happen. I've got to

7:12

assume his family wants it to happen.

7:14

His record label who has him under

7:16

contract wants it to happen. Bingo.

7:20

And it's striking that this happened in

7:22

Nashville, Nashville, Tennessee being the first state

7:24

that passed the law attempting to protect

7:26

the rights of artists to their voice

7:28

against supplications, the elder sides or whatever

7:30

that was passed a little while ago.

7:33

Kristen, how did this strike you both

7:35

as an individual data point, but also in the

7:37

broader conversation of how certain

7:39

artists are starting to, dare

7:42

I say, weaponize AI in their own favor?

7:44

I thought this was a really fascinating use

7:46

case. This is not the first time that

7:49

we've seen kind of something like this happen. Maybe

7:52

it was six months ago now, but

7:54

Edith Piaf, the old French singer, La

7:56

Vie en Rose, she passed away in

7:58

1966. So she

8:01

has been gone. And

8:03

her estate worked with Warner Music

8:05

Group and this film company, and

8:07

they're going to essentially resurrect her

8:09

voice using an AI voice model

8:11

and old recordings. And

8:14

they're going to use that to help narrate

8:16

and create this, I'm pretty sure it's like

8:18

an animated documentary about her life. And

8:20

they're also using AI to help recreate

8:23

her likeness. I find that

8:25

to be really fascinating because

8:27

when you think about it, I think that consensus

8:29

is at the core of whether or not

8:32

we feel like these things are okay. And

8:34

that comes back in Randy Trapp's instance as

8:36

well. But with someone who's truly

8:39

been deceased for 70 years, I don't know, she

8:41

could not have

8:44

conceived of the internet, let alone

8:46

AI, because she's been gone for

8:48

so long. So how do we

8:50

really know whether or not these

8:52

individuals would have ever been okay with this?

8:55

That being said, in an estate situation,

8:58

legally, those decision-making powers have been

9:00

passed down to probably someone else

9:03

in her family. I'm not sure

9:05

exactly. With Randy, it's a little bit

9:07

different because he's still here. And

9:09

as long as he's of sound mind and

9:12

he's able to consent to it, then

9:14

I think that's okay. But it's been

9:16

really interesting. My mom is a very

9:19

big avid watcher of CBS Sunday morning.

9:22

And she called me after that came on because she

9:24

knows I cover AI and music. And

9:27

she was saying, I feel like

9:29

this isn't Randy Travis. To me,

9:31

this is not Randy Travis. And

9:33

I thought that was interesting because when I heard

9:35

it, I considered it in my

9:38

brain as Randy Travis. So when I

9:40

heard it, I was like, yeah, this is the new Randy

9:42

Travis song. It was using AI to assist it. But

9:44

she made a really good point. She was like, there was

9:46

a session singer who sang it.

9:48

And then they essentially used a voice filter

9:51

to map that voice, his timbre,

9:53

his tone over someone

9:55

else's voice who did a different performance.

9:58

That was not Randy. And I

10:00

don't think that either of us is right

10:02

and wrong. It's just interesting how people

10:05

can take away from this very

10:08

different things based on understanding the

10:10

process of how it's done. But

10:12

I do think that in

10:14

general, we feel differently about this. If the

10:16

artist is consenting to it versus if they're

10:18

not. And I also do think as

10:21

far as whether Randy Travis himself is

10:24

consenting truthfully because of

10:26

the nature of his injury, we actually,

10:28

I feel like we don't 100% totally

10:30

understand the depth of his consent, even

10:32

though he's consenting enough to appear on

10:34

CBS Sunday morning, or at least the

10:36

people who are advocating for him are

10:38

putting him on CBS Sunday morning. There's

10:40

also, I got a press release the

10:42

other day about a tour, a Randy

10:44

Travis tour, and I was like, what

10:47

is happening here? But what that, the tour

10:49

is, is this session singer, who

10:52

I guess I had not prior previously heard

10:54

of, but maybe sort of sings in a Randy

10:56

Travis motif, seeing the hits

10:58

of Randy Travis interspersed with like

11:00

biographical films and stuff, and Randy

11:03

Travis will be there, I guess.

11:05

And it's also, this is also maybe

11:08

not coincidentally, this is a Warner project

11:10

as well, so maybe this is an

11:12

indication that Warner as a label is

11:14

stepping out and taking more risks. It

11:17

reminds me a little bit, this is a forgive,

11:19

forgive this OG popcast take, which

11:21

I do not expect you guys to

11:23

know. But like when Luke Combs covered Fast

11:25

Car last year, like my running joke on

11:28

the show was like, it's a Luke Combs

11:30

AI cover. Like he didn't change a thing.

11:32

Like it's literally just Fast Car plugged

11:34

into a machine and someone pressed the Luke

11:37

Combs button and then they sang. And then,

11:39

and then, and then it's it. Nothing else

11:41

happened. And at the time I said, I

11:43

would not be surprised if record labels looking

11:45

for additional commercial angles

11:47

for their artists, especially artists

11:49

who maybe are in the mature phase

11:51

of their career, maybe post peak hit

11:53

making, if they would not say, Hey,

11:56

what are the 30 essential

11:58

songs of the eighties? fire

12:00

them up in the machine and put the Luke Combs filter

12:02

on and just see if anything sounds good. See if anything

12:04

we want to put out. That's

12:07

what I thought. I was like, that's the

12:09

worst case scenario. The worst case scenario is

12:11

we're going to get like a hundred different

12:13

versions of a guy like Luke Combs singing

12:15

a song like Fascar. But

12:17

actually the Randy Travis thing is

12:19

like lightly more insidious and Christian

12:21

to your point, what

12:24

part of that were maybe more to your mother's

12:27

point, what part of

12:29

this is Randy Travis, right? Like

12:31

the vocal is not the

12:34

songwriting. It's not. It's not written by Randy

12:36

Travis. It's written by songwriters for Randy Travis

12:38

X amount of years ago. The

12:41

vocal tone is computer

12:43

approximated. What

12:45

part of that is Randy Travis? I

12:48

truly don't know. And I wonder

12:50

you guys must be

12:52

encountering philosophical questions of this

12:54

nature over and over and over again. So

12:57

I wonder on the one hand

12:59

what part of that is Randy Travis. I'm curious

13:01

about both of your answers. And also the second

13:03

question is does it matter if

13:06

it is quote unquote Randy Travis.

13:08

It's Randy Travis in quotes. Does

13:11

any of the philosophical concern or

13:14

curiosity matter if it

13:16

somehow successfully lands between the quote mark?

13:19

I think that there's actually going to be

13:21

a shift in how we view this

13:23

over time. And I think there already has been.

13:26

If we look back to about a year ago,

13:28

that's when I think music related to AI had

13:30

its first big moment with Ghostwriter with

13:32

his fake Drake song. RIP Ghostwriter.

13:35

Yeah. You

13:37

had a great run. Big run. Big run. Big run. Got a

13:39

great run. And I think that was

13:41

a huge moment when it happened. It made

13:43

all the major news networks. A lot of

13:45

places didn't even know that there was music

13:48

related AI coming out and that people were

13:50

working on that. And when

13:52

that happened, I think people had

13:55

such an extreme reaction

13:57

to that. And I think that's very merited. It's the

13:59

first time we. never seen it. But fast

14:01

forward a year later and we have the Randy

14:04

Travis thing, we have Eadis Piaf, we have an

14:07

interview with Lauv six months ago. He

14:09

translated one of his songs into Korean

14:12

and then mapped his AI

14:14

voice model over it and released it. To

14:17

be fair, Lauv does sound like an AI

14:19

voice without any AI technology. Like Lauv voice

14:21

is just pretty much AI. You're trying to

14:23

get me in trouble. No,

14:26

no, no. Here's the thing

14:28

about popcast is the guests come on and be

14:30

experts and I get in trouble. That's how this

14:32

works. They know where to

14:34

find. Lauv's people know where to find me.

14:38

I'll expect an email from them later.

14:41

But yeah, the Lauv thing happens. And then

14:43

of course we have Drake and

14:45

I'm sure we'll get to this. The

14:47

Drake Kendrick beef and Drake using Tupac

14:49

and Snoop Dogg's voices. And

14:52

that was done without consent. But

14:54

think about how much less we

14:56

all reacted to when that happened

14:58

versus a year ago with Ghost

15:00

Rider taking Drake actually. It's ironic

15:03

that Drake is the one now

15:05

out here, quote unquote, stealing other

15:07

people's voices when he first had

15:09

his stolen. So I find

15:12

it quite interesting that the goalpost is

15:14

going to move. Also I

15:16

remember feeling with the Ghost Rider moment

15:18

that quibble the big conversation amongst me and

15:20

other hip hop fans and critics

15:22

that I was talking to were very

15:24

preoccupied with all

15:27

of the little things that Drake does

15:29

in songs that you'd never see it

15:31

on like the notation. You'd never

15:33

see it on a lyric sheet, but when you hear

15:36

it, when you feel it, when you hear it and

15:39

identify the places in the Ghost

15:41

Rider song where Ghost Rider failed

15:43

at that. Now, obviously it's

15:45

an accomplishment. It's a big accomplishment. But I remember

15:47

most of my friends were kind of like, ah,

15:49

the way that this word goes into this word,

15:51

like Drake would never do that. He would leave

15:53

a pause between A and B. That's

15:55

how we thought about it. But I think what

15:57

you just said is right, which is That

16:00

was because it was such a novel use case now

16:03

like when Drake

16:05

did and we'll get to the to the

16:07

Kendra beef and but when he did the

16:09

pot snoop thing Yes, I

16:11

could identify all that stuff where he

16:13

failed at like sounding like snoop But

16:15

I no longer expected it it like

16:17

something the goalpost had shift and I

16:20

wonder so Rachel with that in mind

16:22

Do these philosophical concerns matter at

16:24

all or have? consumers

16:26

and listeners Already established

16:28

almost like a parallel category

16:30

like there is drape music

16:32

and then there is quote-unquote

16:35

drape music oh

16:38

That's a good question. I feel like for

16:40

most people this stuff is still so new

16:42

for for one second. Let's step back AI

16:45

generated music or music that has been has used

16:48

AI in some way is Has

16:51

been on for a long time and it is

16:54

it is true that in the past couple

16:56

years It's actually developed quite rapidly in terms of

16:58

being able to sort of like really well

17:00

mimic Human-made music especially like vocals and just layering

17:02

of different things on top of each other

17:04

I feel like the Suno and Yudio in particular

17:07

They really showed the average person like

17:09

how far that stuff has developed in

17:11

the last couple years, but I

17:13

feel like most people Don't

17:16

aren't super familiar with the idea

17:18

of AI generated music and so

17:20

I do think that these questions of what is

17:22

real What is not real? What is artistry? What

17:24

is human? I feel like those things matter and At

17:28

least they matter to me And

17:30

I as a listener. I still want to

17:32

know what's going on Something

17:34

is using AI simply as

17:37

like a tool to build on recording to

17:39

edit something That's a little different from if

17:41

you're wholly generating something and going back to

17:43

this Randy example You said what was it

17:46

40 tracks? Or

17:48

I think the 40 vocals vocal

17:50

stems of 40 Randy Travis

17:52

songs Okay, that seems pretty

17:55

small for a data set to me. I feel

17:57

like 40 of anything does not a large

18:00

that make. So if you had more, if you want to

18:02

make it sound better, add more.

18:05

You mentioned that obviously people have been using

18:07

AI in various forms for a while. Maybe

18:09

can we step back from this current moment

18:11

and go back prior before a year ago?

18:14

What are some of the

18:16

earlier examples of people attempting to bring AI

18:18

technology into the music space before we get

18:20

to this glutt? I think we're like at

18:22

a glutt moment, even if most people don't

18:25

realize we're at a glutt moment, but I

18:27

feel like we're there. What

18:29

was happening two years ago, four years ago,

18:31

dare I say six, eight, 10 years ago

18:33

that set the table for this? I

18:35

dare. Yeah. So I think

18:37

the first time that I as

18:39

a technology journalist became aware

18:41

of using AI

18:44

to wholly generate music would have been

18:46

around 2016 when Google was working on

18:48

what was called Project

18:50

Magenta. And it was a research project and

18:52

it was more like at the time they

18:54

were doing like noodling on a piano. And

18:56

it kind of blows my mind when I

18:58

think about what you can do now very

19:00

easily and cheaply versus what was then state

19:02

of the art. And at that time they

19:05

couldn't get AI to form a coherent piece

19:07

of music. It never ended. It was just

19:09

kind of like tickling the ivories, which seemed

19:11

really cool at the time. It was a

19:13

jam band? Google was it? It was just

19:15

a jam band? It's a jam band.

19:17

It's just a piano. Yeah, basically. It was just kind of keep

19:19

going. And I kept being like, Oh, I hope they release it,

19:21

but they would, they never released it. And then it

19:24

kind of there are a few developments

19:26

over the years. OpenAI actually had a

19:28

project called Jukebox. I feel like nobody

19:30

noticed it because it came out at

19:32

the very beginning of the pandemic. It was like,

19:35

I think it was like mid March 2020. I

19:38

was on maternity leave. So I obviously was like,

19:40

whatever, I don't care. But they were trying to,

19:42

they were using like major artists names and trying

19:45

to generate music at the time. It sounds really

19:47

weird. If you want to, if you go online

19:49

and look up OpenAI Jukebox, you'll find like a

19:51

bunch of samples and it's like, Whoa, what is

19:53

this? But yeah, over the past few

19:56

years with the rise of different

19:58

kinds of generative models, AI, generated

20:00

voices, getting better and better. It's kind of like a

20:03

few different pieces of technology coming

20:05

together to create what we

20:07

have now. People like the

20:09

UDO and Suno teams kind of putting all

20:11

these pieces together in a really smart way.

20:14

Before we take that any further, we're gonna

20:16

take a break real fast. Going into this

20:18

break, hear something from

20:20

UDO. UDO, this is a song, it

20:22

comes with song titles.

20:25

The song is City Sounds Unbound. This

20:27

is from a prompt asking for a

20:29

pop cast theme song in the style

20:31

of 90s New York hip-hop. I will

20:33

say this is a little bit more

20:35

salt and pepper than 90s New York

20:38

hip-hop. It's giving 1987 to 1989,

20:42

maybe more, but it does have that spare

20:46

crisp percussion. It does

20:49

have that sassy vocal

20:51

presentation. Again, it's great

20:54

lulz. So this is City Sounds Unbound pop

20:56

cast theme song. We'll be back in a

20:58

minute. I'm

21:20

always something new. Craft

21:29

matters in small ways like how coffee is

21:31

made. Or how

21:33

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22:05

use the New York Times Games app

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22:10

With Connections I need to twist my brain to

22:12

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England, Sandwich is a city in England, Reading

22:18

is a city in England, and I'm going to

22:21

guess Derby is a city in England. I started

22:23

Wordle 194 days ago and I haven't missed a

22:25

day. The New York Times Games app has

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all the games right there. I absolutely

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love spelling bee. I always

22:31

have to get genius. I've

22:33

seen you yell at it and say that. That

22:36

should be a word. Totally should be a

22:38

word. Sudoku is kind of my version of

22:40

lifting heavy weights at the gym. At this point

22:42

I'm probably more consistent with doing the crossword than

22:44

brushing my teeth. When I can finish

22:46

a hard puzzle without hints, I feel like

22:48

the smartest person in the world. When I

22:50

have to look up a clue to help me, I'm

22:53

learning something new. It gives me joy

22:55

every single day. Start playing in the New

22:57

York Times Games app. You can

23:00

download it at nytimes.com/games app.

23:06

We've mentioned Yudio and Suno a couple times.

23:08

These are, it seems like, the two industry

23:10

leaders at the moment in terms of, and

23:12

for those who are listening who have not

23:14

had a chance to play around with it,

23:17

I do recommend just toying around.

23:19

You can make a bunch of songs, at least for

23:21

free. If you're curious about the technology, the

23:23

Popcast theme song at the beginning

23:26

was made with Suno.

23:28

The songs that you'll hear kind of

23:30

sprinkled throughout were made with either Suno

23:32

or Yudio. First of all, on

23:35

a baseline level, you go

23:38

to the interface and you say, I would like a

23:40

theme song for Popcast, the New York Times podcast in

23:43

a style of blank or

23:46

whatever. The lyrics are about this. Or maybe

23:48

in one case, in Yudio's case, you can

23:50

actually write some lyrics better than the song

23:52

will be built around. But

23:55

can we talk a little bit about what's

23:57

underneath the hood? Because obviously, this is something

23:59

that... neither company I

24:01

think has said there is

24:03

a large model that this is trained

24:05

on that these programs are trained on.

24:08

What do we know about those models? We

24:10

don't know that much about the training process

24:13

of these. They've been very tight-lipped about it.

24:15

Of course there's quite a few models kind

24:17

of looking at AI more broadly that have

24:19

been fairly open about the fact that their

24:22

data sets include copyrighted works. I

24:24

think in music because the entire music business

24:26

is based off of exploiting

24:29

copyrights and making money off

24:31

of private ownership of songs.

24:33

This is an extremely

24:36

important thing for music

24:39

lovers as well as musicians and

24:41

labels and publishers to know about and

24:43

they've been pretty quiet about it so

24:46

I think that definitely has rubbed some

24:48

people the wrong way. We don't know

24:50

if it includes copyrighted works. There is

24:52

a former stability AI

24:55

VP of audio who left

24:57

the company and he's founded his

24:59

own nonprofit. It's called Fairly Trained. His name

25:01

is Ed Newton-Rex and basically he's kind of

25:03

made it his mission to talk

25:06

about the training process of AI and music

25:08

and he did do I think it was

25:10

an op-ed for Music

25:13

Business Worldwide where he talked about how

25:15

he was able to

25:17

generate things that sounded

25:19

extremely close to true

25:21

copyrights songs that we all

25:24

know and love by prompting Suno and

25:26

the Udeo enough that they could get

25:28

around to getting these copyrighted works pretty

25:30

explicitly. So it does seem like that

25:32

is a very good possibility to be

25:35

part of the training set but their

25:37

terms and conditions at least for Udeo

25:39

which I checked out recently does put

25:42

the onus on users. So if the user

25:44

wants to release a song let's say it

25:46

has a melody in it that's copyright from

25:48

a copyrighted song and it's bar

25:50

for bar or note for note rather and they

25:53

put it up there. Do a little soldier

25:55

boy joke for all the ads. On

26:01

Spotify and something were to happen and you

26:03

were to get sued, I do believe that

26:05

Onus would be on you, given the terms

26:07

and conditions. So that's definitely something to keep

26:09

in mind when using these things. Also

26:12

one thing that if I think this came

26:14

up in maybe was it

26:16

Brian Hyatt's Rolling Stone story about Suno

26:19

interviewing one of the investors and if it's wrong, if

26:21

I'm wrong, tell me, but I think interviewing one of

26:23

the investors who essentially said, I number

26:26

one, if this company already had

26:28

deals with record labels, I wouldn't

26:30

invest. Like on

26:32

the one hand, I don't want to know

26:34

exactly what the training model is and also

26:37

it's better if we're not in bed with

26:39

the record labels and the publishers at this

26:41

point. But it does seem clear,

26:44

much like Spotify itself or

26:46

TikTok or eventually these programs, they

26:49

will be in business with the

26:51

record labels. That's what it feels

26:53

like inevitability. These kinds

26:56

of relationships will be woven into artist

26:58

contracts, be woven into songwriter contracts or

27:00

producer contracts. Is it your understanding that

27:02

that's something that's actively in motion or

27:04

is that still feel one, two, three,

27:06

five years on the road? That

27:08

is happening. There are

27:10

definitely talks going on. We may also use lawsuits,

27:12

but there are definitely some talks going on. I

27:16

think that the ideal situation for the

27:18

majors right now is I

27:20

think what it seems to be

27:22

their strategy is picking and choosing

27:24

certain music, AI companies to anoint

27:27

as the ones that they want to succeed. Given

27:30

they own the vast majority

27:32

of important copyrights in music history,

27:34

which is honestly for recorded

27:36

music, a relatively short history, I think

27:39

they're trying to control the outcome

27:41

and veer it in a certain

27:43

direction. They certainly want

27:45

to participate in getting licenses

27:48

for their works if that's

27:50

what's needed, but we'll

27:53

see what happens. I do think there

27:55

is a possibility of a future where

27:57

Suno and Udeo become so

27:59

entrenched. in the creative process and

28:01

become so popular that it could force

28:03

the hands of music companies

28:06

to come to the table and work with them

28:08

even though they might right

28:10

now not be interested in that.

28:13

But in the near term, I do think that kind

28:15

of these more quote unquote fairly trained models

28:18

that use licensed works or

28:20

they make their training data

28:22

in-house even by hiring musicians to make

28:24

a bunch of samples for them. I

28:27

think that ideally that's what they're looking

28:29

for. Is that

28:31

what's happening? Do you think that they're

28:34

essentially rather than if they're not training

28:36

on publicly available or commercially available music,

28:38

they're essentially hiring session musicians to be

28:41

like, play me a hardcore song,

28:43

play me an emo song, play me this? A

28:46

lot of different models trained in different

28:48

ways. Like there's an AI

28:50

music company called Soundful and they train

28:52

on one shot. So that's

28:54

one type of thing instead of a loop. A

28:56

lot of people train on loops or I'm also

28:58

seeing a lot of people

29:01

are turning to production libraries. So people

29:03

who make music that's cheap

29:05

to be licensed for TV, film, YouTube

29:07

videos, et cetera. And they're

29:10

licensing those catalogs and that

29:12

can contain up to a million works, which

29:14

it really puts a dent in things when

29:16

you're trying to get there. And but yeah,

29:18

there are people who are hiring musicians just

29:21

to feed the machine right now, which I

29:23

think is a very interesting idea. As

29:25

a musician, do you feel like you're training

29:28

models to replace you in certain

29:32

things? If these AI models get good

29:34

enough, do they replace production libraries? Are

29:36

the production libraries and these musicians contributing

29:38

to speeding that up or is this

29:40

all inevitable? And it's better

29:42

to just get the money in the short term

29:45

and take the bet on the long term. I've

29:48

got to assume those musicians are under NDAs

29:50

if they're doing that. But if not, or

29:52

if you want to break them, email anybody

29:54

on this show. We'd love to hear more

29:56

about that process. OK,

29:59

let me play. doubles advocate for a second

30:01

because one thing that happened after the Ghost Rider song,

30:03

or at least

30:06

one thing I was thinking about, was let's

30:08

take Drake. Drake is incredibly

30:11

famous, incredibly successful,

30:13

and someone who

30:16

genuinely engages in the

30:18

meme ecosystem about Drake,

30:21

both positive memes, negative memes. Drake

30:24

understands how to make

30:26

songs, how to create visual

30:29

content, and also how to

30:31

react to the inevitable kind

30:33

of like effluvia on the

30:35

internet that is made non-consensually

30:37

about you. If I'm

30:39

Drake, why don't I just

30:41

make the Drake app which

30:43

can have varying levels of AI

30:45

technology. The cheapest level is

30:47

just Drake vocal filter. It's like we can run

30:50

through this podcast through whatever that

30:52

vocal filter is, and it just sounds like three Drake's talking

30:54

to each other. The second level may

30:56

be a higher level of training

30:58

with song construction and more

31:00

idiosyncrasies. Maybe the highest level is some

31:03

combination of that and then actually get

31:05

to interacting with people who make OVO

31:07

records to make it sound exactly like

31:10

a Drake song. Why

31:12

shouldn't that be a monetizable

31:15

income stream that a

31:17

smart artist would take advantage of?

31:19

What's the what's the downside of

31:21

that? Oh

31:24

man, there's a lot to unpack there.

31:28

If you're an artist, I've been thinking about this a

31:30

lot lately because I've been covering OpenAI and Scarlett

31:33

Johansson's anger about OpenAI having a voice

31:35

for chat TPT that sounds similar to

31:37

her voice or that she believes firmly

31:39

sound similar to her and a lot

31:41

of people also sound similar to her.

31:44

And I just keep thinking about how valuable

31:47

your voice is when you are various

31:49

types of artists if you're an actor.

31:51

Obviously if you are a singer, your

31:53

voice is valuable to you and also in

31:55

some cases like Drake, I think we can argue

31:58

that it's iconic, right? People can recognize it. They

32:00

can hear it and go, oh, that's obviously

32:02

this artist. So when you get

32:04

to that level, which select a few people

32:06

are, I feel like

32:08

it must be a very complicated thought

32:11

process of do I want to monetize? Like we are

32:13

getting to a point where you can totally build an

32:15

app like that. It would be still quite a bit

32:17

of work to make it sound really good, but you could totally

32:19

do it. But

32:23

to Kristen's earlier point about do

32:25

we participate now? Should I get the

32:27

money for this now or not? I

32:29

feel like it must be very tricky to decide what

32:31

to do there. But do you really want to

32:33

not have control over your voice? I feel like

32:35

a lot of people would say, at least for

32:37

now, no. But won't that

32:40

happen anyway? Because

32:42

how far away is the technology where someone

32:45

could just do that and not have to

32:47

pay anybody to sound like Drake? Like

32:49

why wouldn't an artist proactively, it's

32:52

already there basically. So

32:54

why wouldn't an artist get out? Like in

32:56

my mind, one of the

32:58

downsides is obviously you have a bad actor, right?

33:00

You have someone who uses it to make

33:02

Drake say something objectionable. Like think about

33:04

cameo and people on cameo being told

33:06

to be like, say something and then

33:08

it turns into white supremacist dog whistle

33:10

or something. And obviously you don't want

33:12

the AI version of that. But

33:15

barring that, assuming there's some customer,

33:17

there's some intervention between you creating the

33:19

thing and being able to share it

33:21

publicly, why wouldn't this

33:24

be a good idea for someone who's

33:26

incredibly famous and is already going to

33:28

get meme slash AI'd? Kristen, what

33:30

do you think? I mean, I think

33:32

that there are some artists who are

33:34

already leaning in and trying

33:36

to find controlled ways to do this.

33:39

But I think that it's a whole spectrum. And I

33:41

think at the end of the spectrum of being very fast

33:43

and loose about this is like grinds. Making

33:46

her own AI model last year, she was

33:48

very, very early on this. I think she

33:50

was inspired by what happened with Ghost Rider.

33:52

I know she was tweeting about that at

33:54

the time. And then shortly thereafter, released her

33:56

own voice model and said basically, I don't

33:58

care what y'all do with it. You can even

34:00

release it commercially if you want, but I want 50% of

34:03

whatever royalties you make from it. I've

34:05

since talked to some other AI voice

34:07

companies that are hoping to do kind

34:09

of official partnership type stuff as

34:12

their business model. And

34:14

some of them have thought that there's not a

34:17

ton of commercial value so far that we've

34:19

seen from voice models. So

34:21

like none of those grimes AI songs that her

34:23

fans made, I haven't heard of

34:25

any of them making good money.

34:27

There's one by Keto, K-I-T-O, using

34:30

the AI grimes model. That's the only one

34:32

in the streaming economy. I don't even know how

34:35

much that made. But

34:37

some people are thinking about monetizing it at

34:39

the root. So whenever your voice is

34:41

used by a fan and that fan pays

34:43

a subscription fee to the service, then you

34:45

get paid on that conversion.

34:48

People are thinking of all sorts of ways to try to

34:51

make this work for artists. I think

34:53

the challenge is being a really

34:55

good artist is curating yourself and

34:57

selling a brand version of yourself. And I

34:59

feel like that's never been more true than

35:02

an age of social media and

35:04

where we're at today. I think people really

35:07

want to feel like their

35:09

artist is someone who's like a guiding light.

35:11

They know exactly who they are as a

35:13

person and as an art

35:16

maker. So I think

35:18

that this does get into slippery slope

35:20

territory of when you start

35:22

letting your fans pretend to be you. Do

35:25

we really trust them to mark and say, this

35:27

is AI? Do we really trust them to

35:29

follow the rules? But yeah, you

35:31

could even argue, though, that we lost control of

35:33

who we are on the internet a long time

35:35

ago. That's sort of

35:37

my feeling. My feeling is, no, I don't trust fans

35:39

any more than I trust trolls

35:41

or trust meme makers. Everybody

35:45

is fundamentally untrust. Everybody who's not

35:47

the artist themselves is fundamentally untrustworthy.

35:49

And I wonder if the next

35:51

phase of this

35:54

is going in artistry broadly,

35:56

not simply in music across

35:58

disciplines is essential. essentially, how do

36:00

we monetize the mistrust that's

36:03

already baked into online presentation of

36:05

art? So that's on the one hand. The

36:08

lesson goal side of me says, let's

36:11

say it's not a full Drake app like what I

36:13

was describing, but let's say it's essentially

36:15

an audition app. It's

36:18

I have a song that I think Drake should

36:20

sample or I have a vocal pattern that I

36:22

think he might find useful. This I can see

36:24

working really well in Nashville, which is very heavily

36:26

a songwriter culture and demos are

36:29

pitched around constantly. Why

36:32

not have a company and says, Hey, I'm

36:34

pitching this to Carrie Underwood. Here's the demo

36:36

in Carrie Underwood voice rather than hiring some

36:38

random demo singer to sing it how they

36:40

think Carrie Underwood might sing it. That

36:43

feels like a semi valid use case

36:45

for some of this technology. It's

36:48

already being done that way. There's

36:50

a lot of songwriters that are

36:52

using AI voice filters privately, which

36:55

I feel a lot better about knowing that they're

36:57

not being commercially released. It's kind

36:59

of not a ton of harm. The

37:01

only harm is potentially upsetting the artist by them

37:03

receiving a demo and they're like, what the hell?

37:06

Why am I on this track? I never recorded. I

37:09

sound terrible. Yeah. So

37:11

yeah. I mean, like, who knows the session vocalist might have

37:13

not nailed the performance in

37:16

the style of you, but yeah, you're

37:18

already seeing a lot of songwriters. I

37:20

think I reported on this last summer. So it's been about

37:23

a year of people doing this. And so

37:25

it's a way to land demos. It is

37:27

really, really hard to pitch a record

37:29

and actually get it to land. And

37:32

for a lot of songwriters, they'll do anything to try to

37:34

make it better. Before AI,

37:36

during my reporting of this, I found

37:39

one songwriter who told me that he has

37:41

this go to guy that whenever he's pitching

37:43

to Adam Levine, Maroon 5, he

37:46

has an Adam Levine sound like session

37:48

singer that he'll get his demos recorded

37:50

with. And that's the darkest thing I've

37:53

ever been said on Popcast. The

38:00

poor person out there is an

38:02

entire metier as Adam Levine sound-alike

38:04

demos. Man, phrase up for you, bro.

38:07

This guy also has a go-to Justin Bieber

38:09

vocalist. Like nothing said, slightly.

38:15

But at least the argument would be like, well,

38:17

at least in that instance, you're hiring a person

38:19

to do a job where they get paid. But

38:22

these guys are saying that session vocalists only make $100 to $250

38:24

for... That's

38:27

kind of negligible side money for these people usually.

38:30

So yeah, now people are using ad voice

38:33

filters to try to better target pitch records.

38:35

I've seen with some people they'll include like

38:37

a folder to the NR that represents the

38:39

artist and in the folder will be the

38:42

AI version and the clean just regular demo

38:44

version so they can pick based

38:46

on what the artist prefers,

38:48

which I think is probably the smartest way

38:50

to go about it without freaking someone out.

38:52

But people are expecting this now. So I

38:55

think it's less shocking

38:57

than even a year ago. Rachel,

39:00

can we talk a little bit about legislation? Can

39:02

we talk about what's happened in Tennessee? But

39:05

also how legislation

39:07

is actually going to interact with some of

39:09

these philosophical questions because I may be

39:13

overly cynical in the sense that I

39:15

think I accept that there is some

39:17

disaggregation of the self that happens when

39:19

you present creative things in an online

39:21

space and famous people

39:23

who are discussed and memed

39:26

intensely, probably somewhere

39:29

in their spirit understand that what's

39:31

happening on the internet is 70% of them

39:34

or 30% or 90% or

39:37

at any given moment it's shifting. But

39:39

obviously legislation is not that nuanced. And

39:42

I do think it's important that some of

39:44

these things are enshrined in law. I wonder

39:46

if you could talk about what happened in Tennessee

39:49

and then maybe some of the other things

39:51

that are starting to happen about how to

39:53

address protecting an artist's

39:55

voice legally. There's

39:57

a lot of interesting stuff

39:59

happening. legally like all across

40:01

generative AI. With the music

40:04

stuff, as you mentioned earlier, there's the Elvis

40:06

Act in Tennessee. Gotta love an act named

40:08

after the king. I just thought that was

40:10

really funny. You have to have that heavy

40:13

draw when you talk about it. I apologize.

40:17

But so like that in particular

40:19

I thought was very interesting. The

40:21

aim of that is to protect

40:23

musicians' rights. They want to protect

40:25

them from AI impersonations in particular

40:27

in a place like Tennessee that

40:30

has such a heavy music, huge

40:32

music scene, huge music history, obviously

40:34

very focused on the humans that

40:36

are making the music, either singing

40:39

or just instrumenting. And so it

40:41

does make sense that a place like Tennessee would come

40:43

up with legislation like this. I think it's the only,

40:45

there are very, like in general, there are very few

40:47

laws in the United States related

40:50

to AI in

40:52

general. There are a handful that

40:54

are related to like specific applications

40:56

of technology. In Illinois, they

40:59

have a law called BIPA, which is

41:01

aimed at protecting people from unauthorized use

41:03

of biometric data, for instance. But like

41:05

you don't see much. And so this Elvis

41:07

rule I thought was very interesting. What I'm wondering

41:09

about is how they're going to enforce it. Like

41:12

how, what is considered an artist under

41:14

the law or someone with a recognizable

41:16

voice? I mean, they're saying this rule

41:18

is meant to protect people from unauthorized

41:20

AI, like reproductions of your voice.

41:22

If you have a recognized voice, you don't want

41:25

someone to just be able to make a new

41:27

one. So how do you decide whose

41:29

voice is, like is there a threshold for like

41:31

who's recognizable as an artist? I'm still a little

41:33

unclear on that. And then also how do you,

41:36

what are you going to do when someone complains?

41:38

And where do both offending parties have to

41:40

be in Tennessee? So like, I think it's

41:42

an interesting idea. I have a lot of

41:44

questions. I think that what

41:47

we're starting to see overall is a

41:49

bunch of efforts, both at the federal

41:51

level, at the state level, of people

41:53

trying to regulate different types

41:55

of generative AI. So AI

41:58

that's generating text, generating. sounds

42:00

such as music, generating images, and a

42:02

lot of the stuff is aimed at

42:04

the training data. So should the

42:07

prevailing law regarding training

42:09

data scraped from the internet, which we

42:11

have traditionally considered fair use, should that

42:13

stay or should that change? We might

42:16

see that changing by medium. That's going

42:18

to be interesting to see. So it's

42:20

possible that a court would say companies

42:22

like Suno and Yudio can continue to

42:24

scrape the internet forever for free to

42:26

do whatever, but maybe something

42:28

that's doing generative AI for images cannot.

42:30

Like I've talked to some legal experts

42:32

about that and so it's very

42:35

sticky right now. What's gonna happen with the

42:37

inputs, what's gonna happen with the outputs, and I think

42:39

it's gonna take years for this to be resolved in

42:41

any way. We're gonna take a quick break right now.

42:43

Here's another popcast theme song.

42:46

This one is a Suno generation. This

42:48

is the second generated song

42:50

when I asked a very big

42:53

picture prompt for a popcast theme song,

42:55

not specifying genre, but I think implying

42:57

pop. This is sort of a light

43:00

electro pop. Feels a little

43:02

bit European. It's giving Cascada.

43:05

It's giving Gigi

43:09

D'Agostino. So anyway, here's

43:11

this pop two from Suno pop

43:13

casting song. Families

44:12

have a lot going on. Let

44:15

Ollie help manage the mental load with

44:17

new cognitive health supplements for everyone 4

44:19

and up like delicious lollie focus pops

44:22

or lollymellopops for kids. And

44:24

for parents, try 3 new brainy juice to

44:26

help you focus, chill out, or get energized.

44:29

Find these cognitive health buddies for the whole

44:31

fam at ollie.com. These

44:34

statements have not been evaluated by the Food and

44:36

Drug Administration. This product is not intended to diagnose,

44:38

treat, store, or prevent any disease. We

44:44

have the beginning of the

44:46

legal conversation about what's protectable, who and

44:48

how it's enforced. On some level, I've

44:50

got to assume that the AI industry

44:53

is also going to go on, if

44:55

it hasn't already, something of

44:57

a marketing blitz. And

44:59

when I was alluding to the tears of AI,

45:01

like, is there good AI and bad AI? Is

45:07

there funny AI and serious AI?

45:10

With Ghostwriter and there was

45:12

that website or the channel that I emailed

45:14

you guys there I ruined it, or it's

45:16

the Beach Boys covering 99 problems. Oh,

45:19

oh, oh. On some level, is

45:22

the AI industry going to use

45:24

simple, accessible, winky, winky stuff

45:26

as like, I see AI as your

45:28

friend. It's just fun what we're

45:30

doing here. While underneath,

45:34

much more sinister and disruptive things

45:36

are happening. Because that's, I feel

45:38

like we're already seeing the tearing

45:40

of AI between kind of like

45:43

publicly legible uses of AI,

45:46

and then far more abstruse

45:48

and powerful uses of AI

45:50

underneath. Is that just Suno

45:52

and UDO marketing, essentially? It's being like, here's a

45:54

fun AI song, you guys should love it. And

45:57

then you guys pay attention to that while we

45:59

do the video. dirty work? In

46:01

general, kind of. I think it's more a little

46:04

more complicated than that. But yeah, if you think

46:06

back a couple years when there was a

46:08

big backlash against facial recognition technology,

46:10

you saw a lot of companies

46:13

saying, please regulate us. We want to

46:15

be regulated, yet nobody is coming up

46:18

with the rules. And I think you're

46:20

seeing a similar thing, and we have seen over

46:22

the past year or so, a lot of

46:24

it is like application based, right? It's not AI

46:26

generally because it's become so vast and there's so

46:29

many different applications of what in the past we

46:31

would have just thought of as like machine learning.

46:33

But I think with the music stuff, I

46:36

think it looks like the companies are looking more

46:38

for partnerships. But yeah, I

46:40

think there definitely is, like the companies will say, please

46:42

regulate us. But what they mean is, let us help

46:44

you come up with the rules, because of course then

46:46

the rules, it's sort of a Fox and the Hennihaus

46:49

kind of situation. Let us help you come up with

46:51

the rules, and those rules will necessarily

46:53

be rules that we're okay

46:55

with. And they will probably benefit us,

46:57

perhaps like a startup that's working on

46:59

closed source models, wants rules that help

47:02

regulate open source models, for instance. We've

47:05

talked a lot about AI as a song

47:07

making tool or as a tool to help

47:09

a person who makes songs make songs. AI

47:12

is being used in a bunch of other

47:14

ways in the music business, it's being used

47:16

in play listing, other kinds of

47:18

large data model training. Can you talk a little

47:20

bit about where's AI happening

47:22

that we're not seeing? Everybody,

47:25

again, we know about BBL

47:27

Jersey, we know about Drake rapping as Tupac

47:29

and Snoop. Everybody knows about

47:31

that. And I think, to your point,

47:33

Rachel, the AI industry would be very

47:35

happy if that's where public understanding of

47:38

AI music stopped. What's

47:40

happening underneath that we should be

47:42

mindful of? I think

47:44

that there's a lot of different applications of AI in

47:46

the music business today that we don't talk about that

47:49

often. The stuff that's not generative,

47:51

the stuff that's not about music creation,

47:53

that stuff is also happening

47:55

in a variety of ways. I think one

47:58

of the most interesting and... potentially

48:00

helpful use cases for AI

48:02

that we haven't talked about yet

48:05

is royalty collection and processing. That's

48:07

just notoriously a huge pain in

48:09

the ass. And there's,

48:11

given there's so many different

48:14

little microtransactions every single time you stream

48:16

a song, and then there's in a

48:18

case of certain rap songs, it

48:20

could be with a bunch of samples. It

48:22

could be up to like 30 songwriters. So

48:25

then you have to divide that all up

48:27

between all the right songwriters, get the money

48:29

to them, get the money to their publisher.

48:31

It's a mess. And

48:34

I think a lot of people think we could be doing better

48:36

in the music industry, getting

48:38

correct metadata and kind of making sure

48:41

to clean that stuff up. But

48:43

in general, I do think that given there's

48:45

just such a large, there's trillions

48:47

of lines of transactions to process,

48:50

AI will certainly be helpful in

48:52

that case. And also, because it's

48:54

so challenging, and makes it really

48:56

hard for artists and songwriters to

48:58

audit their record labels and music

49:01

publishers. And so I've heard

49:03

from some business managers that they're

49:05

like really hoping that this is going to be

49:07

a way to put

49:09

some checks and balances on that and really sort

49:11

through what their royalty statements are

49:13

looking like. And in addition,

49:16

you can see on a place like

49:18

Spotify, they've integrated the AI DJ feature,

49:20

which is pretty fun. I could see

49:22

it being interesting in the future. In

49:25

addition, they also have this beta

49:27

AI play

49:29

listing tool where you can type in kind of

49:32

a vibe, and then it will generate

49:34

a list of tracks. And I think that's fun

49:36

and playful. For now,

49:39

I don't really think that it's that

49:41

exciting right now. But maybe it could be in

49:44

general with AI that interacts with

49:46

the music business and interactive music

49:48

creation. A lot of this stuff,

49:50

we're still figuring out what the actual use cases

49:52

will be long term. Are some of these things

49:54

just gimmicks for kids that are

49:57

just having fun on the internet? Or are there actual

49:59

applications? that will be commercially

50:01

valuable, we don't know

50:03

yet. I think that we're trying

50:06

every single time that I'm talking to people,

50:08

I'm always asking them what ways are they

50:11

using it that's actually going to be helpful

50:13

for them or helpful for their fans. But

50:15

yeah, there are quite a few things

50:17

including this AI DJ, AI playlisting

50:20

features that Spotify have that are just kind of

50:22

playful and fun and we'll just see where it

50:24

goes from there. I haven't tried

50:26

that although it does make me want to see if

50:29

it could figure out how to recreate

50:32

what I played on my college radio show in 1995.

50:34

If I just give it a few problems and be

50:36

like this is what my radio show was like and

50:38

it was about can you sort of like

50:40

loosely estimate what a playlist was like. John,

50:43

you're too unique for that. I don't

50:45

think it could do it. That's exactly

50:47

right. They weren't gonna put the quiet

50:50

storm in between the backpack wrap. They

50:52

weren't gonna do that but I did

50:54

that. That's right. Rachel,

50:56

what about you? Do you

50:58

think there are either

51:01

good AI or nefarious use cases that

51:04

are lurking underneath the like high-five look

51:06

at the joke we just made AI

51:08

that people seem to be talking about?

51:11

I think there are always, this is like

51:13

a really unsatisfying answer, but I feel like

51:15

there are always good and bad uses for

51:17

pretty much any technology and AI is absolutely

51:20

no exception. You can't really say this is

51:22

good, this is bad categorically because different people

51:24

have different ideas. I think that what

51:26

we're seeing with its use in the music

51:28

industry is as Kristen said there's still a

51:30

lot of figuring it out but at the

51:32

same time I think it's interesting

51:35

that like one of the

51:37

uses of AI that the average person

51:39

is most familiar with just is related

51:41

to like song selection on Spotify. If

51:44

it's just creating like

51:46

a radio station that's sort of tuned

51:48

to you, I still find that kind

51:50

of like weirdly magical. Using that on

51:53

Spotify or like Netflix I'm like how

51:55

do they always know what I want? Well

51:57

obviously it's been trained on a ton of

51:59

data. And every time I use it,

52:01

I am like giving it yet more information about

52:03

me that it can then mine to keep me

52:05

glued to it in the future. That's

52:07

a good thing and a bad thing, right? So a

52:10

lot of these uses of AI are going

52:12

to be a combination of both. And I

52:14

feel like a lot of what we can

52:16

do as consumers, we're journalists, but we also

52:18

use these things. I think it's just important

52:20

to be really mindful of what is going

52:22

on behind the scenes as much as we

52:24

can be. And then obviously as journalists, we

52:26

have to interrogate them and tell everybody about

52:28

it. As we go

52:30

out, is there for either of you a

52:32

particular, whether it's a song or

52:34

a particular moment that you've encountered in your

52:37

reporting that you think people should know about

52:39

that maybe they don't know, but that's not

52:41

one of the kind of like 10 layering,

52:43

red alarm screening AI

52:45

use cases the last 12 months. Is there

52:47

anything you want to point people to to

52:50

say, this is interesting, fascinating or

52:52

clever that people don't know? I

52:55

have one. Okay. I

52:57

think, and maybe

52:59

this might have just inspired me to actually write

53:01

a story on it, but I have

53:04

been talking with a bunch of artist managers

53:06

who have said that the worst thing that

53:08

you can ever have to get your artist

53:10

to do is radio liners. It's like that,

53:12

Hey, this is Kristen and you're listening to

53:14

KISS FM. They

53:17

hate that. It's like pulling teeth.

53:19

And I very briefly worked at a record label where I was sent

53:21

out to do that. And it was

53:23

actually horrible. So I have heard

53:26

that some managers have tried using

53:28

AI to turn in AI radio

53:31

liners. Wait, did I read that in one of yours?

53:33

I feel like I read about that in someone's story.

53:35

Was it one of your stories? So

53:38

I like made a very quick mention of it

53:40

as like a bullet point in a newsletter that

53:42

I just started. Follow it. Machine

53:44

learning, billboard.com. So yeah,

53:47

so, but I haven't done a full story on that. And I feel like

53:49

now I should now that we're talking about

53:51

it, but I do think that that's really

53:54

a fascinating way to streamline the process of

53:56

music promotion, make your artists more

53:58

available. That being said, if I was. radio

54:00

station and I figured out that almost

54:02

the liners I was getting were faked,

54:05

I'd be pissed. So I don't know. I actually, Loki,

54:07

don't know if I'd be pissed. Also, they might want

54:09

to make one for podcasts. Like by all means, send

54:11

one over. I don't care if it's AI. We'll

54:14

start this... It would be hilarious if it was

54:16

probably funnier if it was AI. Can

54:19

we start this podcast with Adam Levine, AI? No,

54:24

just ask the guy, the real session musician.

54:27

No, I'm a higher than Adam

54:29

Levine guy. Yo, that's going to

54:32

be my ultimate anniversary, like my

54:34

10 years on Popcast whenever

54:36

that happens. Totally so nice. I'm a higher

54:38

than Adam Levine guy to sing a podcast

54:40

theme song in the voice of Adam Levine,

54:42

one of the artists I have been absolutely

54:45

the cruelest to in my critical career. But

54:47

anyway, if anyone wants to say AI,

54:49

shout out, hilarious. I'll probably play it.

54:51

Rachel, anything that you want to draw

54:53

folks through? One thing

54:55

that I did when I was working on a

54:58

feature about AI music recently and about Suno and

55:00

UDO in particular was near the end of the

55:02

process after playing around with them, I went on

55:04

to Spotify because I was just curious if these

55:07

things were starting to trickle in there and just

55:09

search for the word Suno. I would

55:11

recommend that people do that and just kind of

55:13

see... You can't guarantee that the stuff you're

55:15

finding is made using Suno, but a lot of

55:17

it sure sounds like it. There's still sort

55:19

of a certain tone to these things and

55:22

like kind of a slight weirdness to the

55:24

song. The way that the songs

55:26

progress, you're like, that's not exactly what one

55:28

would expect. But it is a nice way to

55:30

get a sense for what people happen to be

55:32

doing with it. That's sort of like percolating on

55:34

Spotify. So that would be my suggestion besides trying

55:36

these out for yourself is just go on Spotify

55:38

and search for Suno or maybe search for UDO.

55:40

There's probably stuff from there on there too at

55:42

this point. One thing that we

55:44

didn't actually explicitly get to are differences between

55:47

Suno and UDO. And I do think it's

55:49

worth saying. So I, in making a pop

55:51

cast theme song, which we've been hearing throughout

55:53

the episode, I put the same prompts into

55:55

Suno and UDO, basically

55:58

Cotton Bass. Maybe I left. out some

56:00

punctuation, but essentially the same prompts. One

56:03

thing I felt with UDO is

56:05

it returned over and over again to

56:08

the same lyrical themes. I didn't give

56:10

any lyric prompts. I only gave topic

56:12

prompts. There was Beats and

56:14

Rhymes came up a lot in the

56:17

UDO ones, maybe three different ones

56:20

in UDO used that or a

56:22

version of that phrasing, whereas I

56:24

thought the Suno lyric generation felt

56:27

a little bit more natural. Also,

56:30

on the whole, I felt like

56:33

the styles that it approximated

56:35

better were styles that I

56:37

already, maybe it's just my

56:39

association, already associate with a

56:41

kind of degree of digital

56:43

texture, electro-pop or certain strains

56:45

of hip-hop, whereas things that

56:47

are a little bit more guitar driven or

56:50

fundamentally melodic driven, I felt

56:52

they struggled more with. I wonder,

56:54

do you guys ultimately,

56:56

I think Suno was more

56:58

effective than UDO for me in my

57:01

task? Before we go, do you guys

57:03

see the difference or feel the difference between the

57:06

two and where do you land? I definitely noticed

57:08

some big differences between the two when I was

57:10

playing around with them. For me, Suno felt a

57:12

little bit more intuitive to use. One

57:15

thing that I would note is Suno

57:17

uses chat GPT to generate

57:19

lyrics. So it's working with open AI technology.

57:21

UDO off the top of my head, I'm

57:23

not sure, but I do know that Suno

57:26

uses chat GPT. So if you

57:28

like the feel of chat GPT, I think we

57:30

can all agree it has a style. That's

57:33

where they're pulling from and then it brings

57:35

back the song lyrics and also song

57:37

titles, I think, are all coming back.

57:39

And then they're sort of like musicifying

57:41

it. UDO, meanwhile, I think also the

57:44

way they build the songs in UDO,

57:46

in the kinds of chunks that they

57:48

build, I found it a little bit

57:50

more challenging to use. But I could

57:52

also see how someone who has a

57:54

greater understanding of music and song structure

57:56

might actually find that more appealing. And

57:59

the stuff that I've made I guess I've found

58:01

a few more things in Suno that I've

58:03

liked, but usually I'll create my own lyrics

58:06

and just see where that takes me. So

58:08

I don't know if that's made a difference, but

58:11

I think they're both extremely advanced. I think

58:14

one thing I don't think we explicitly

58:16

said so far is that

58:19

most music-related generative AI models that

58:21

are out there today, either

58:24

they do the voice or

58:26

they do the track, not both. And

58:30

to see that Suno and Udo are

58:32

doing both is really remarkable. And something

58:34

I have only seen probably

58:36

in the last, I don't know, since the start of 2024-ish.

58:40

But I think they're definitely neck and

58:42

neck. That being said, something that should

58:44

be noted about Suno is they just

58:46

raised $125 million in their latest funding

58:48

round. And

58:52

Udo, I'm pretty sure, as late as funding round,

58:54

raised $10 million. That being

58:56

said, who knows what their

58:59

financials look like, why Suno wanted to raise so much,

59:01

all that stuff. I'm not sure. But

59:03

I am really curious to see what Suno

59:05

comes up with with all the money that

59:08

they have just gotten from investors. So

59:10

I'm really curious to see if in the six months

59:12

from now we're going to be talking about

59:14

them being neck and neck, or

59:16

if one of them will pull away. But I

59:18

guess it should be noted that also BBL Drizzy

59:20

was made on Udo. And that

59:23

turned out to be quite good and

59:25

is something that I feel like I

59:27

hear people humming and singing all

59:29

the time. Yeah, the most commercially

59:32

successful or publicly recognizably successful AI

59:34

generated the track thus far. And

59:37

to my point earlier about Drake, he just found a way

59:39

to rap on it. So I'm just

59:41

saying, any free ideas out here on

59:43

Popcat. Rachel Metz, Krista Robinson, thanks for

59:45

going into the brave new world with

59:48

us. I'm confident we're going to be

59:50

back talking about this again probably sooner

59:52

than we're all comfortable with. Thank

59:55

you so much for having us. And that

59:57

is our show, What a Ride.

59:59

It has been every Popcat. ever

1:00:01

is at nytimes.com/popcast. Popcast

1:00:03

Deluxe with me and Joe is

1:00:05

at YouTube, youtube.com/popcast and subscribe all

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across the board. Email

1:00:10

us, popcast at nytimes.com. Get

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the Facebook group, tinyurl.com/popcast discord

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or slash popcast Facebook. The

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stickers are at itsthepopcast.myshopify.com.

1:00:23

There's a Zazzle shop. I put

1:00:25

some mugs in there, some buttons, some baby

1:00:28

onesies. Go nuts, knock yourself out. We're gonna

1:00:30

have more on the merch stuff soon. We

1:00:32

will let you know. As

1:00:34

always, our producers Pedro Rosado from Head

1:00:36

Stepper Media. We'll be back

1:00:38

next week. Let's go out with

1:00:41

another UDO generated popcast theme song.

1:00:43

This is also made

1:00:45

to the general prompt for a theme song, sort

1:00:47

of in a pop style. Somehow

1:00:50

this is extremely British. This

1:00:52

is very dry 90s,

1:00:54

light, a little bit sour

1:00:56

even. British-esque

1:00:58

presentation of a pop song. This

1:01:01

is Tune In, Feel

1:01:03

Good, popcast theme song. ♪

1:01:06

I'm a young girl from P.T.C.

1:01:09

Ukraine and the Polkies. ♪ ♪

1:01:13

Ain't been feeling any good. ♪ ♪

1:01:16

So tune in to P.T.C. for

1:01:19

this little group. ♪ ♪

1:01:21

I'm a little bit like you should.

1:01:23

♪ ♪

1:01:27

I'm a little bit like you should. ♪