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Speaker 1

00:00

The following is a conversation with Gustav Sørenstrøm. He's the Chief Research and Development Officer at Spotify, leading their product design, data technology, and engineering teams. As I've said before, in my research and in life in general, I love music, listening to it and creating it. And using technology, especially personalization through machine learning to enrich the music discovery and listening experience.

Speaker 1

00:27

That is what Spotify has been doing for years, continually innovating, defining how we experience music as a society in a digital age. That's what Gustav and I talk about among many other topics including our shared appreciation of the movie True Romance, in my view 1 of the great movies of all time. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, give it 5 stars on iTunes, support on Patreon, or simply connect with me on Twitter at Lex Friedman, spelled F-R-I-D-M-A-N.

Speaker 1

01:01

And now, here's my conversation with Gustav Söderström.

Speaker 2

01:06

Spotify has over 50 million songs in its catalog, so let me ask the all-important question. I feel like you're the right person to ask. What is the definitive greatest song of all time?

Speaker 3

01:21

It varies for me personally.

Speaker 2

01:24

So you can't speak definitively for everyone.

Speaker 3

01:27

I wouldn't believe very much in machine learning if I did. Right. Because everyone had the same taste.

Speaker 2

01:34

So for you, what is you have to pick? What is the song?

Speaker 3

01:38

It's it's pretty easy for me. There is this song called You're So Cool, Hans Zimmer, soundtrack to True Romance. It was a movie that made a big impression on me and it's kind of been following me through my life.

Speaker 3

01:52

Actually, I had to play at my wedding. I sat with the organist and helped him play it on an organ, which was a pretty, Pretty interesting experience.

Speaker 2

02:01

That is probably my, I would say, top 3 movie of all time. Yeah, it's just an incredible movie.

Speaker 3

02:08

Yeah. And it came out during my formative years. And as I've discovered in music, you shape your music taste during those years. So it definitely affected me quite a bit.

Speaker 2

02:18

Did it affect you in any other kind of way?

Speaker 3

02:21

Well, the movie itself affected me back then. It was a big part of culture. I didn't really adopt any characters from the movie, but it was it was a great story of love, fantastic actors.

Speaker 3

02:33

And and, you know, really, I didn't even know who Hans Zimmer was at the time, but fantastic music. And so that song has followed me and the movie actually has followed me throughout my life.

Speaker 2

02:44

That was Quentin Tarantino, actually, I think, director, director of produced that. So it's not Stairway to Heaven or Bohemian Rhapsody.

Speaker 3

02:52

It's those are those are great. They're not my personal favorites, but I've realized that people have different tastes and that's that's a big part of what we do.

Speaker 2

03:00

Well, for me, I don't have to stick with Stairway to Heaven. So 35,000 years ago, I looked this up on Wikipedia, flute-like instruments started being used in caves as part of hunting rituals, in primitive cultural gatherings, things like that. This is the birth of music.

Speaker 2

03:18

Since then, we had a few folks, Beethoven, Elvis, Beatles, Justin Bieber, of course, Drake. So in your view, let's start like high level philosophical. What is the purpose of music on this planet of ours?

Speaker 3

03:35

I think music has many different purposes. I think there's certainly a big purpose, which is the same as much of entertainment, which is escapism, and to be able to live in some sort of other mental state for a while. But I also think you have the opposite of escaping, which is to help you focus on something you are actually doing.

Speaker 3

03:57

As I think people use music as a tool to tune the brain to the activities that they are actually doing. And it's kind of like, in 1 sense, maybe it's the rawest signal. If you, if you think about the brain as neural networks, it's maybe the most efficient hack we can do to actually actively tune it into some state that you want to be. You can do it in other ways.

Speaker 3

04:21

You can tell stories to put people in a certain mood, but music is probably very effective to get you to a certain mood very fast.

Speaker 2

04:28

You know, there's a social component historically to music, where people listen to music together. I was just thinking about this that to me, and you mentioned machine learning, but to me personally, music is a really private thing. I'm speaking for myself, I listen to music, almost nobody knows the things I have in my library, except people who are really close to me and they really only know a certain percentage, just like some weird stuff that I'm almost probably embarrassed by.

Speaker 2

05:00

Right.

Speaker 3

05:01

It's called the guilty pleasures. Right. Everyone has

Speaker 2

05:03

the guilty pleasures. Yeah. Hopefully they're not too bad.

Speaker 2

05:05

But it's for me, it's personal. Do you think of music as something that's social or is something that's personal? Does it vary?

Speaker 3

05:16

So I think it's the same. It's the same answer that you use it for for both. We've we've thought a lot about this during these 10 years at Spotify, obviously, in 1 sense, as you said, music is incredibly social.

Speaker 3

05:31

You go to concerts and so forth. On the other hand, it is your escape and everyone has these things that are very personal to them. So what we've found is that When it comes to, most people claim that they have a friend or 2 that they are heavily inspired by and that they listen to. So I actually think music is very social, but in a smaller group setting, it's an intimate form of, It's an intimate relationship.

Speaker 3

06:03

It's not something that you necessarily share broadly. Now at concerts, you can argue you do, but then you've gathered a lot of people that you have something in common with. I think this broadcast sharing of music is something we tried on social networks and so forth, but it turns out that people aren't super interested in what their friends listen to. They're interested in understanding if they have something in common, perhaps with a friend, but not just as information.

Speaker 2

06:35

Right. That's really interesting. I was just thinking of it this morning, listening to Spotify. I really have a pretty intimate relationship with Spotify, with my playlists.

Speaker 2

06:47

Right. I've had them for many years now and they've grown with me together. There's an intimate relationship you have with a library of music that you've developed. And we'll talk about different ways we can play with that.

Speaker 2

07:02

Can you do the impossible task and try to give a history of music listening from your perspective from before the Internet and after the Internet and just kind of everything leading up to streaming Spotify? So I'll try.

Speaker 3

07:19

It could be a 100 year podcast.

Speaker 2

07:21

But yeah,

Speaker 3

07:22

I'll try to do a brief version. There are some things that I think are very interesting during the history of music, which is that Before recorded music, to be able to enjoy music, you actually had to be where the music was produced, because you couldn't record it and time shift it, right? Creation and consumption had to happen at the same time, basically concerts.

Speaker 3

07:42

And so you either had to get to the nearest Village to listen to music. And while that was cumbersome and it severely limited the distribution of music, it also had some different qualities, which was that the creator could always interact with the audience. It was always live. And also there was no time cap on the music.

Speaker 3

08:01

So I think it's not a coincidence that these early classical works, they're much longer than the 3 minutes. The 3 minutes came in as a restriction of the first wax disc that could only contain a 3 minute song on 1 side, right? So actually the recorded music severely limited the, or put constraints. I won't say limit.

Speaker 3

08:22

I mean, constraints are often good, but it put very hard constraints on the music format. So you kind of said like, instead of doing these, this opus on like many, you know, tens of minutes or something. Now you get 3 and a half minutes because then you're out of wax on this disc. But in return, you get an amazing distribution.

Speaker 3

08:40

Your reach will widen, right?

Speaker 2

08:41

Just on that point real quick. Without the mass scale distribution, there's a scarcity component where you kind of look forward to it. We had that, it's like the Netflix versus HBO Game of Thrones.

Speaker 2

08:58

You like wait for the event because you can't really listen to it. So you like look forward to it and then it's, you derive perhaps more pleasure because it's more rare for you to listen to a particular piece. You think there's value to that scarcity?

Speaker 3

09:13

Yeah, I think that that is definitely a thing. And there's always this component of if you have something in infinite amounts, will you value it as much? Probably not.

Speaker 3

09:23

Humanity is always seeking some... Is relative. So you're always seeking something you didn't have, and when you have it, you don't appreciate it as much. So I think that's probably true.

Speaker 3

09:32

But I think that's why concerts exist. So you can actually have both. But I think net, if you couldn't listen to music in your car driving, that'd be worse. That cost would be bigger than the benefit of the anticipation, I think, that you would have.

Speaker 2

09:48

So, yeah, it started with live concerts, then it's being able to, you know, the phonograph invented, right? That you start to be able to record music.

Speaker 3

10:00

Exactly. So then then you got this massive distribution that made it possible to create 2 things. I think, first of all, cultural phenomenons, they probably need distribution to be able to happen. But it also opened access to, you know, for a new kind of artists.

Speaker 3

10:16

So you started to have these phenomenons like Beatles and Elvis and so forth. That were really a function of distribution, I think, obviously of talent and innovation, but there was also a technical component. And of course, the next big innovation to come along was radio, broadcast radio. And I think radio is interesting because it started not as a music medium, it started as an information medium for news.

Speaker 3

10:41

And then radio needed to find something to fill the time with so that they could honestly play more ads and make more money and music was free. So so then you had this massive distribution where you could program to people. I think those things, that ecosystem is what created the ability for for for hits. But it was also a very broadcast medium.

Speaker 3

11:02

So you would tend to get these massive, massive hits, but maybe not such a long tail.

Speaker 2

11:08

In terms of choice of everybody listening to the same stuff.

Speaker 3

11:11

Yeah, and as you said, I think there are some social benefits to that. I think for example, there's a high statistical chance that if I talk about the latest episode of Game of Thrones, we have something to talk about just statistically. In the age of individual choice, maybe some of that goes away.

Speaker 3

11:27

So I do see the value of like, you know, shared cultural components, but I also obviously love personalization.

Speaker 2

11:37

And so let's catch this up to the internet. So maybe Napster, well, first of all, there's like MP3s, tapes, CDs.

Speaker 3

11:45

There was a digitalization of music with a CD, really. It was physical distribution, but the music became digital. And so they were files, but basically boxed software, to use a software analogy.

Speaker 3

11:57

And then you could start downloading these files. And I think there are 2 interesting things that happened back to music used to be longer before it was constrained by the distribution medium. I don't think that was a coincidence. And then really the only music genre to have developed mostly after music was a file again on the internet is EDM.

Speaker 3

12:18

And EDM is often much longer than the traditional music. I think it's interesting to think about the fact that music is no longer constrained in minutes per song or something. It's a legacy of an old distribution technology. And you see some of this new music that breaks the format.

Speaker 3

12:34

Not so much as I would have expected, actually, by now, but it still happens.

Speaker 2

12:39

So, first of all, I don't really know what EDM is.

Speaker 3

12:42

Electronic dance music. Yeah, you could say Avicii was 1 of the biggest in this genre.

Speaker 2

12:47

So the main constraint is of time, something

Speaker 3

12:51

like

Speaker 2

12:51

3, 4 or 5 minutes on. So you could

Speaker 3

12:53

have songs that were 8 minutes, 10 minutes and so forth, because, you know, it started as a digital product that you downloaded. So you didn't have this constraint anymore. So I think it's something really interesting that I don't think has fully happened yet, we're kind of jumping ahead a little bit to where we are.

Speaker 3

13:11

But I think there's there's tons of formative innovation in music that should happen now that couldn't happen when you needed to really adhere to the distribution constraints. If you didn't adhere to that, you would get no distribution. So Björk, for example, the Icelandic artist, she made a full iPad app as an album. That was very expensive.

Speaker 3

13:34

Even though the app store has great distribution, she gets nowhere near the distribution versus staying within the 3 minute format. So I think now that music is fully digital inside these streaming services, there is the opportunity to change the format again and allow creators to be much more creative without limiting their distribution ability.

Speaker 2

13:55

That's interesting that you're right. It's surprising that we don't see that taken advantage more often. It's almost like the constraints of the distribution from the 50s and 60s have molded the culture to where we want the 5, 3 to 5 minutes on that anything else, not just So we want the song as consumers and as artists.

Speaker 2

14:18

Like, because I write a lot of music and I never even thought about writing something longer than 10 minutes. That's really interesting that those constraints.

Speaker 3

14:29

Because all your training data has been 3 and a half minutes.

Speaker 2

14:31

Sounds right. It's right. Okay.

Speaker 2

14:33

So yeah. Digitization of data led to the MP3s.

Speaker 3

14:38

Yeah. So I think you had this file then that was distributed physically, but then you had the components of digital distribution and then the internet happened and there was this vacuum where you had a format that could be digitally shipped but there was no business model. And then all these pirate networks happened. Napster and in Sweden, Pirate Bay, which was 1 of the biggest.

Speaker 3

15:03

And I think from a consumer point of view, which kind of leads up to the inception of Spotify, from a consumer point of view, consumers for the first time had this access model to music where they could, without kind of any marginal cost, they could try different tracks. You could use music in new ways. There was no marginal cost. And that was a fantastic consumer experience to have access to all the music ever made, I think was fantastic.

Speaker 3

15:34

But it was also horrible for artists because there was no business model around it. So they didn't make any money. So the user need almost drove the user interface before there was a business model. And then there were these download stores that allowed you to download files, which was a solution, but it didn't solve the access problem.

Speaker 3

15:55

There was still a marginal cost of 99 cents to try 1 more track. And I think that that heavily limits how you listen to music. The example I always give is, you know, in Spotify, a huge amount of people listen to music while they sleep, while they go to sleep and while they sleep. If that costed you 99 cents per 3 minutes, you probably wouldn't do that.

Speaker 3

16:15

And you would be much less adventurous if there was a real dollar cost to exploring music. So the access model is interesting in that it changes your music behavior. You can be, you can take much more risk because there's no marginal cost to it.

Speaker 2

16:28

Maybe let me linger on piracy for a second. Cause I find, especially coming from Russia, piracy is something that's very interesting to me. Not me of course ever, but I have friends who have partook in piracy of music, software, TV shows, sporting events.

Speaker 2

16:53

And usually to me what that shows is not that they're, they can actually pay the money and they're not trying to save money. They're choosing the best experience. So what to me piracy shows is a business opportunity in all these domains. And that's where I think you're right.

Speaker 2

17:12

Spotify stepped in is basically piracy was an experience. You can explore, find music you like, and actually the interface of piracy is horrible.

Speaker 3

17:26

Bad metadata.

Speaker 2

17:28

Yeah, bad metadata.

Speaker 3

17:29

Long download times, all kinds of stuff.

Speaker 2

17:31

And what Spotify does is basically first rewards artists and second makes the experience of exploring music much better. The same is true, I think, for movies and so on. Piracy reveals In the software space, for example, I'm a huge user and fan of Adobe products.

Speaker 2

17:50

And there was much more incentive to pirate Adobe products before they went to a monthly subscription plan. And now all of the said friends that used to pirate Adobe products that I know now actually pay gladly for the monthly subscription.

Speaker 3

18:08

I think you're right. I think it's a sign of an opportunity for product development and that sometimes there's a product market fit before there's a business model fit in product development. I think that's a sign of it.

Speaker 3

18:23

And in Sweden, I think it was a bit of both. There was a culture where we even had a political party called the Pirate Party. And this was during the time when, when people said that, you know, information should be free. It's somehow wrong to charge for ones and zeros.

Speaker 3

18:40

So I think people felt that artists should probably make money somehow else and, you know, concerts or something. So at least in Sweden, it was part really social acceptance, even at the political level and that, but that also forced Spotify to compete with, with free, which, which I don't think would actually could have happened anywhere else in the world. The music industry needed to be doing bad enough to take that risk. And Sweden was like the perfect testing ground.

Speaker 3

19:06

It had government funded high bandwidth, low latency broadband, which meant that the product would work. And it was also there was no music revenue anyway. So they were kind of like, I don't think this is going to work, but why not? So this product is 1 that I don't think could have happened in America.

Speaker 3

19:23

The world's largest music market, for example.

Speaker 2

19:25

So how do you compete with free? Because that's an interesting world of the internet where most people don't like to pay for things. So Spotify steps in and tries to, yes, compete with free.

Speaker 2

19:39

How do you do it?

Speaker 3

19:40

So I think 2 things. 1 is people are starting to pay for things on the Internet. I think 1 way to think about it was that advertising was the first business model because no 1 would put a credit card on the internet.

Speaker 3

19:52

Transactional with Amazon was the second and maybe subscription is the third. And if you look offline, subscription is the biggest of those. So That may still happen. I think people are starting to pay, but definitely back then we needed to compete with free.

Speaker 3

20:05

And the first thing you need to do is obviously to lower the price to free. And then you need to be better somehow. And the way that Spotify was better was on the user experience, on the actual performance, the latency of, you know, even if you had high bandwidth broadband, it would still take you 30 seconds to a minute to download 1 of these tracks. So the Spotify experience of starting within the perceptual limit of immediacy, about 250 milliseconds, meant that the whole trick was it felt as if you had downloaded all of Pirate Bay.

Speaker 3

20:41

It was on your hard drive. It was that fast, even though it wasn't. And it was still free, but somehow you were actually still being a legal citizen. That was the trick that Spotify managed to pull off.

Speaker 2

20:54

So, I've actually heard you say this or write this, and I was surprised that I wasn't aware of it, because I just took it for granted. You know, whenever an awesome thing comes along, you're just like, oh, of course it has to be this way. That's exactly right, that it felt like the entire world's libraries at my fingertips because of that latency being reduced.

Speaker 2

21:15

What was the technical challenge in reducing the latency?

Speaker 3

21:19

So, there was a group of really, really talented engineers. 1 of them called Ludwig Stregius, he wrote the, actually from Gothenburg, he wrote the initial, The Utorrent client, which is kind of an interesting backstory to Spotify, you know, that we have 1 of the top developers from BitTorrent clients as well. So he wrote Utorrent, the world's smallest BitTorrent client.

Speaker 3

21:43

And then He was acquired very early by Daniel and Martin, who founded Spotify, and they actually sold the Utorrent client to BitTorrent, but kept Ludwig. So Spotify had a lot of experience within peer-to-peer networking. So the original innovation was a distribution innovation, where Spotify built an end-to-end media distribution system. Up until only a few years ago, we actually hosted all the music ourselves.

Speaker 3

22:10

So we had both the service side and the client. And that meant that we could do things such as having a peer-to-peer solution to use local caching on the client side, because back then the world was mostly desktop.

Speaker 2

22:22

But

Speaker 3

22:22

we could also do things like hack the TCP protocols, things like Nagel's algorithm for kind of exponential back off or ramp up and just go full throttle and optimize for latency at the cost of bandwidth. And all of this end to end control meant that we could do an experience that felt like a step change. These days we actually are on GCP.

Speaker 3

22:46

We don't host our own stuff And everyone is really fast these days. So that was the initial competitive advantage. But then obviously you have to move on over time.

Speaker 2

22:53

And that was over 10 years ago, right?

Speaker 3

22:56

That was in 2008, the product was launched in Sweden. It was in a beta, I think 2007.

Speaker 2

23:01

And it was on the desktop, right?

Speaker 3

23:02

So that's the only

Speaker 2

23:03

there's no phone There

Speaker 3

23:05

was no phone the iPhone came out in 2008 But the App Store came out 1 year later, I think so the writing was on the wall, but there was no phone yet

Speaker 2

23:15

You've mentioned that people would use Spotify to discover the songs they like and then they would torrent those songs just so they can copy it to their phone. Just hilarious. Exactly.

Speaker 2

23:28

Not torrent, piracy. Seriously, piracy does seem to be like a good guide for business models. Video content, as far as I know, Spotify doesn't have video content.

Speaker 3

23:40

Well, we do have music videos and we do have videos on the service. But the way we think about ourselves is that we're an audio service. And we think that if you look at the amount of time that people spend on audio, it's actually very similar to the amount of time that people spend on video.

Speaker 3

23:58

So the opportunity should be equally big. But today is not at all valued. Video is valued much higher. So we think it's basically completely undervalued.

Speaker 3

24:07

So we think of ourselves as an audio service. But within that audio service, I think video can make a lot of sense. I think for When you're discovering an artist, you probably do want to see them and understand who they are, to understand their identity. You don't see the video every time, no, 90% of the time the phone is gonna be in your pocket.

Speaker 3

24:25

For podcasters, you use video. I think that can make a ton of sense. So we do have video, but we're an audio service where think of it as we call it internally, backgroundable video. Video that is helpful but isn't the driver of the narrative.

Speaker 2

24:39

I think also if we look at YouTube, the way people, there's quite a few folks who listen to music on YouTube. So in some sense, YouTube is a bit of a competitor to Spotify, which is very strange to me that people use YouTube to listen to music. They play essentially the music videos, right?

Speaker 2

25:00

But don't watch the videos and put it in their pocket.

Speaker 3

25:03

Well, I think I think it's similar to to what's strangely, maybe it's similar to what we were for the piracy networks where YouTube for historical reasons have a lot of music videos. So people use YouTube for a lot of the discovery part of the process, I think. But then it's not a really good sort of, quote unquote, MP3 player, because it doesn't even background.

Speaker 3

25:30

Then you have to keep the app in the foreground. So so the consumption is not a good consumption tool, but it's a decent, good discovery. I mean, I think YouTube is fantastic products and I use it for all kinds of purposes. That's true.

Speaker 3

25:40

So

Speaker 2

25:41

if I were to admit something, I do use YouTube a little bit for the discovery to assist in the discovery process of songs. And then if I like it, I'll add it to Spotify.

Speaker 3

25:50

But that's OK. That's OK with us.

Speaker 2

25:53

OK, so sorry, we're jumping around a little bit. So this kind of incredible, you look at Napster, look at the early days of Spotify. How do you, 1 fascinating point is how do you grow a user base?

Speaker 2

26:06

So you're there in Sweden, you have an idea. I saw the initial sketches that look terrible. How do you grow a user base from a few folks to millions?

Speaker 3

26:19

I think there are a bunch of tactical answers. So first of all, I think you need a great product. I don't think you take a bad product and market it to be successful.

Speaker 3

26:30

So you need a great product.

Speaker 2

26:31

But sorry to interrupt, but it's a totally new way to listen to music too. So it's not just did people realize immediately that Spotify is a great product?

Speaker 3

26:39

I think they did. So back to the point of piracy, it was a totally new way to listen to music illegally. But people had been used to the access model in Sweden and the rest of the world for a long time through piracy.

Speaker 3

26:50

So 1 way to think about Spotify, it was just legal and fast piracy. And so people have been using it for a long time. So they weren't alien to it. They didn't really understand how it could be legal because it would seem too fast and too good to be true, which I think is a great product proposition, if you can be too good to be true.

Speaker 3

27:08

But what I saw again and again was people showing each other, clicking the song, showing how fast it started, and saying, can you believe this? So I really think it was about speed. Then we also had an invite program that was really meant for scaling because we hosted our own servers. We needed to control scaling, but that built a lot of expectation and I don't want to say hype because hype implies that it wasn't true.

Speaker 3

27:34

No. Expectations. Excitement. Excitement around the product.

Speaker 3

27:38

And we've replicated that when we launched in the US. We also built up an invite-only program first. So lots of tactics, But I think you need a great product that solves some problem. And basically, the key innovation, there was technology, but on a meta level, the innovation was really the access model versus the ownership model.

Speaker 3

27:58

And that was tricky. A lot of people said that they wanted to own their music, they would never kind of rent it or borrow it. But I think the fact that we had a free tier, which meant that you get to keep this music for life as well, helped quite a lot.

Speaker 2

28:14

So This is an interesting psychological point that maybe you can speak to. It was a big shift for me. It's almost like I had to go to therapy for this.

Speaker 2

28:26

I think I would describe my early listening experience, and I think a lot of my friends do, as basically hoarding music. As you're slowly, 1 song by 1 song, or maybe albums, gathering a collection of music that you love and you own it. It's like often, especially with CDs or tape, you like physically had it. And what Spotify, what I had to come to grips with, it was kind of liberating actually, is to throw away all the music.

Speaker 3

28:55

I've had this therapy session with lots of people. And I think the mental trick is, so actually we've seen the user data when Spotify started, a lot of people did the exact same thing. They started hoarding as if the music would disappear, right?

Speaker 3

29:09

Almost the equivalent of downloading. And so, you know, we had these playlists that had limits of like a few hundred thousand tracks and we figured no 1 will ever. Well, they do. It's in hundreds and hundreds of thousands of tracks.

Speaker 3

29:21

To this day, some people want to actually save quote-unquote and play the entire catalog. But I think that the therapy session goes something like instead of throwing away your music, if you took your files and you stored them in a locker at Google, it'd be a streaming service. It's just that in that locker, you have all the world's music now for free. So instead of giving away your music, You got all the music.

Speaker 3

29:46

It's yours. You could think of it as having a copy of the world's catalog there forever. So you actually got more music instead of less. It's just that you just took that hard disk and you sent it to someone who stored it for you.

Speaker 3

30:00

And once you go through that mental journey of like, still my files, they're just over there. And I just have 40 million of them, 50 million or something now. Then people are like, okay, that's good. The problem is, I think, because you paid us a subscription.

Speaker 3

30:13

If we hadn't had the free tier, where you would feel like even if I don't want to pay anymore, I still get to keep them. You keep your playlist forever. They don't disappear even though you stop paying. I think that was really important.

Speaker 3

30:23

If we would have started as, you know, you can put in all this time, but if you stop paying, you lose all your work. I think that would have been a big challenge and was the big challenge for a lot of our competitors. That's another reason why I think the free tier is really important. That people need to feel the security that the work they put in, it will never disappear, even if they decide not to pay.

Speaker 2

30:42

I like it how you put the work you put in. I actually stopped even thinking of it that way. I just actually Spotify taught me to just enjoy music as opposed to as opposed to what I was doing before, which is like in an unhealthy way, hoarding music.

Speaker 2

30:58

Which I found that Because I was doing that, I was listening to a small selection of songs way too much to where I was getting sick of them. Whereas Spotify, the more liberating kind of approach is I was just enjoying, of course I listened to Stairway to Heaven over and over, but because of the extra variety, I don't get as sick of them. There's an interesting statistic I saw. So Spotify has, maybe you can correct me, but over 50 million songs, tracks, and over 3 billion playlists.

Speaker 2

31:31

So 50 million songs and 3 billion playlists, 60 times more playlists than songs. What do you make of that?

Speaker 3

31:39

Yeah, so the way I think about it is that from a statistician or machine learning point of view, you have all these, if you want to think about reinforcement learning, you have this state space of all the tracks. And you can take different journeys through this world. And I think of these as people helping themselves and each other, creating interesting vectors through this space of tracks.

Speaker 3

32:08

And then it's not so surprising that across many tens of millions of kind of atomic units, there will be billions of paths that make sense. And we're probably pretty quite far away from having found all of them. So kind of our job now is users. When Spotify started, it was really a search box that was for the time pretty powerful.

Speaker 3

32:30

And then I like to refer to it as this programming language called playlisting, where if you, as you probably were, were pretty good at music, you knew your new releases, you knew your back catalog, you knew your Star Way to Heaven, you could create a soundtrack for yourself using this playlisting tool, that's like metaprogramming language for music to soundtrack your life. And people who were good at music, it's back to how do you scale the product. For people who are good at music, that wasn't actually enough. If you had the catalog and a good search tool, and you can create your own sessions, you could create really good a soundtrack for your entire life.

Speaker 3

33:01

Probably perfectly personalized because you did it yourself. But the problem was most people, many people aren't that good at music. They just can't spend the time. Even if you're very good at music, it's gonna be hard to keep up.

Speaker 3

33:12

So what we did to try to scale this was to essentially try to build, you can think of them as agents, that this friend that some people had that helped them navigate this music catalog, that's what we're trying to do for you.

Speaker 2

33:26

But also, there is something like 200 million active users on Spotify. So there, it's okay. So from the machine learning perspective, you have these 200 million people plus, they're creating, it's really interesting to think of playlists as I Mean, I don't know if you meant it that way, but it's almost like a programming language.

Speaker 2

33:54

It's a release a trace of exploration of those individual agents of the the listeners And you have all this new tracks coming in. So it's a fascinating space that is ripe for machine learning. So is there is a possible How can playlists be used as data in terms of machine learning to help Spotify organize the music?

Speaker 3

34:25

So we found in our data, not surprising, that people who playlisted a lot, they retained much better. They had a great experience. And so our first attempt was to playlist for users.

Speaker 3

34:37

And so we acquired this company called Tunigo of editors and professional playlisters and kind of leveraged the maximum of human intelligence to help to help build kind of these vectors through the track space for people. And that broadened the product. But then the obvious next, and we used statistical means where they could see when they created a playlist, how did that playlist perform? They could see skips of the songs, they could see how the songs perform, and they manually iterated the playlist to maximize performance for a large group of people.

Speaker 3

35:12

But there were never enough editors to playlist for you personally. So the promise of machine learning was to go from kind of group personalization, using editors and tools and statistics to individualization. And then what's so interesting about the 3 billion playlists we have is, and The truth is we lucked out. This was not a priority strategy, as is often the case.

Speaker 3

35:34

It looks really smart in hindsight, but it was dumb luck. We looked at these playlists and we had some people in the company, a person named Eric Bernadon. He was really good at machine learning already back then, in like 2007, 2008. Back then it was mostly collaborative filtering and so forth.

Speaker 3

35:53

But we realized that what this is, is people are grouping tracks for themselves that have some semantic meaning to them. And then they actually label it with a playlist name as well. So in a sense, people were grouping tracks along semantic dimensions and labeling them. And so could you use that information to find that latent embedding?

Speaker 3

36:18

And so we started playing around with collaborative filtering, and we saw tremendous success with it. Basically trying to extract some of these dimensions. And if you think about it, it's not surprising at all. It'd be quite surprising if playlists were actually random, if they had no semantic meaning.

Speaker 3

36:39

For most people, they group these tracks for some reason. So we just happened to cross this incredible data set where people are taking these tens of millions of tracks and group them along different semantic vectors.

Speaker 2

36:52

And the semantics being outside the individual users, so it's some kind of universal. There's a universal embedding that holds across people on this earth?

Speaker 3

37:02

Yes, I do think that the embeddings you find are going to be reflective of the people who playlisted. So if you have a lot of indie lovers who playlist, your embed is going to perform better there. But what we found was that, yes, there were these latent similarities.

Speaker 3

37:20

They were very powerful. And it was interesting because I think that the people who playlisted the most initially were the so-called music aficionados who were really into music. And their taste was often geared towards a certain type of music. And so what surprised us, if you look at the problem from the outside, you might expect that the algorithms would start performing best with mainstreamers first, because it somehow feels like an easier problem to solve mainstream taste than really particular taste.

Speaker 3

37:54

It was the complete opposite for us. The recommendations performed fantastically for people who saw themselves as having very unique taste. That's probably because all of them playlisted and they didn't perform so well for mainstreamers. They actually thought they were a bit too particular and unorthodox.

Speaker 3

38:10

So we had the complete opposite of what we expected. Success within the hardest problem first and then had to try to scale to more mainstream recommendations.

Speaker 2

38:19

So you've also acquired Echo Nest that analyzes song data. So. In your view, maybe you can talk about so what kind of data is there from a machine learning perspective?

Speaker 2

38:33

There's a huge amount, what we're talking about playlisting and just user data of what people are listening to, the playlist they're constructing, and so on. Then there's the actual data within a song, what makes a song, I don't know, the actual waveforms, is there any, how do you mix the 2? How much value is there in each? To me, it seems like user data is, well, it's a romantic notion that the song itself will contain useful information.

Speaker 2

39:05

But if I were to guess, user data would be much more powerful. Playlists would be much more powerful.

Speaker 3

39:11

Yeah, so we use both. Our biggest success initially was with playlist data without understanding anything about the structure of the song. But when we acquired the Echonest, they had the inverse problem.