Spotify's Plan For AI Generated Music, Podcasts, and Recommendations — With Gustav Söderström

0:00Spotify's chief product officer, chief technology officer, and co-president joins us for a deep conversation about how AI is changing the music industry, podcasts, and audiobooks from recommendations to synthetic content. That's coming up right after this.

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0:47Welcome to Big Technology Podcast, a show for cool-headed, nuanced conversation of the tech world and beyond. We have a great show for you today because we're sitting here in Four World Trade Center, Spotify's New York City headquarters with the company's co-president, chief product officer, and Chief Technology Officer. Yes, all that in one. Gustav Soderstrom is here. Gustav, great to see you. Welcome to Big Technology. Thank you for having me, Alex. It's a pleasure to be here. Very excited. Great to be here. I mean, we're in a beautiful studio in your office. I've been looking around. I just can't believe how amazing the studio is.

1:18And also, it's cool for me to be sitting here with you because I'm using your app every day. And Spotify is the place where I touch some of the most, I wouldn't even call it possessions because I'm subscribed to it but one of the most beloved experiences that i have which is music and so many of us use spotify all the time but we hear from you guys rarely so i do appreciate the opportunity to speak with you me too i try i appreciate that i'm very glad to hear that and i'd love to share as much as i can about how spotify actually works it's sort of a passion of mine to try to explain things and and how they work so i i actually love these podcasts in some ways an app will determine how people experience a format, but in some ways, a moment in time will determine how an app has to deal with the content within it.

2:05And Spotify is going through both of those. Both of those regard artificial intelligence. I don't know if you've heard of Suno. In fact, I'm sure you've heard of Suno. It's one of our favorite things to use on Big Technology Podcast. Ranjan and I, we do this show on Friday. We built a theme song with Suno and played it, and it was a good time.

2:35I'm curious from your perspective, running product, that's Spotify, how do you feel about AI music, AI generated music? Because the songs, they're not amazing, but they're good. There've been some big hits. Do you view this as an opportunity, a threat? Do you want it on your platform? So the way I think about it, I'm a technologist, so obviously I'm very excited about the technology itself. And I love AI. I think it's a super impressive product. It works amazingly well. And it's philosophically very interesting that something we thought was impossible just a few years ago, that a machine could sound like something a human did.

3:14It can be creative. Legitimately incredible. You prompt it and out comes a great sounding song. It is incredible. So I think that technology is amazing. Now, my interest is to think of these technologies as tools. So if you think about music, it's going through a journey of more capable tools. If you go way back, if you were a musical genius, like a Bach or someone, you literally needed access to an orchestra to be able to realize that genius. Even if you could play multiple instruments yourself, you couldn't play them at the same time. So you actually needed like an orchestra. and then we got to recording music and you could record one instrument at a time so you got more and more independent and then somewhere around the 80s the synthesizer came along and made that and meant that you didn't have to be able to play all the instruments yourself you could you could sort of quote unquote fake the drums using the synthesizer and the guitar and so forth so i think there's been this progression of more more powerful tools that enabled more and more creativity and And then somewhere in the 90s, the DAW, the digital audio workstation, came along and being a Swede, very proud of this, someone like Avicii came along.

4:22And what is interesting with Avicii is he was not very proficient at any one instrument or a singer. So in a previous world, he would not have been considered a very creative person because he couldn't realize that. With access to this tool, the digital audio workstation, it turns out he was one of the most creative people we had that we are very, very proud of. so so for for him the digital audio workstation was as steve jobs would say a bicycle for the mind it meant that he could he get more productive and he could he could express his genius and the big question with this next round of tools is the same is it amplifying creativity or is it replacing people and i i think it's amplifying creativity it is giving more and more people the access to be creative.

5:08You need even less motor skills on a piano or something. You need less technical skills in a digital audio workstation. So I think of them as tools. And I think there's this interesting question on what is AI music? I think people say AI music, and they mean something that was prompted with not too much of a prompt and not too much work, so like 100 % AI. But the truth is that much of music being made today is a combination. I think many of the big artists are using AI for parts of their songs, parts of the track with the drums, etc. So I think there's actually a scale between zero AI and 100 % AI.

5:46And I think we're on this this progression where it's actually going to be very difficult to say what is an AI song. Does it have to be 100, 99%, 70%, 50 %? But the real question is, do you welcome this stuff on your platform? Let's say somebody does prompt 100 % AI. Spotify could fill up with songs that are AI prompted. It's very easy to create these songs and then upload them to the internet. How do you feel about those? Do you want them? So there are two questions there. One is, what is Spotify about? We're a tool for creators. And if creators want to use AI to enhance their music, as long as we follow the legislation and copyright laws, we want them to be able to monetize their music and pay out.

6:26So for us, we are trying to support creators. And the music catalog has grown tremendously since we started, from tens of millions of tracks to hundreds of millions of tracks and i think it's going to keep expanding but what i think is important for for us to figure out that i think is our job and the rest of the music industry is if you go back to the years of piracy there was this technology called peer-to-peer and file sharing that was amazing you worked on that early on exactly that exactly we actually incorporated that technology into to spotify but before spotify the technology sort of preceded the business model.

7:03It was great for consumers. They could now get all of this music for free, but it didn't work for creators. And I think we're in the same period of time now where the technology has preceded the business model. So I think the technology is great. I do think we need to find a way for the creators who have participated in this to be reimbursed. So that's something that we are thinking about and the rest of the industry is thinking about. If we can find a business model. I think we could unlock a tremendous amount. So there's a separate question, which is then these models, the way they were trained, will that be considered legal or not?

7:41Which is a legal question that is being decided on some time period. For example, in the US, these companies are now sued. So I think that question will be decided by legislation. But let's assume that there is one of these models, whether it has to be retrained on other data or not. Is that an interesting tool for us if it was trained legally? yes if creators can participate in it so first of all it's good to hear that you're already thinking about issues of compensating creators musicians because you know i write text in addition to podcasting and i know that models have trained on my text and previously i'm not going to see a dime on that um it's a little different right with music but yeah if you can channel different musicians there should be i think some remuneration um but i'm going to just ask one last time on this point then we're going to move on um so meta for instance they have ai generators the feeds have i won't say filled but there's lots of ai generated images they're engaging meta seems to be okay with this it doesn't ban it and now some of the top content on a meta platform is shrimp jesus which sort of combines like two people's great loves which is god jesus and seafood and i've seen that yeah it's it's massive these type of images are massive on meta so from a spotify perspective if these songs generated by ai music generators become engaging and let's say they follow the rules is that good for spotify well i think like this if creators are using this uh these technologies they are creating music in a legal way that we reimburse and people listen to them and they are successful we should let people listen to them i think what is different though i don't think it's our job to generate that music instead of the creators right that's a that's a key difference are we as a platform for creators and then we can have a discussion on which tools are they allowed to use like they could use the other workstation but not lm maybe that's not actually we should we shouldn't decide that for them but there is a question should we generate all the music ourselves and that's where we're saying no we're not going to generate that music and other platforms maybe will because it's cheap content, right?

9:49So that's the key difference of we decided what we want to be in this world and it's a platform for creators. Then there's a question of which tools they are allowed to have, which is partially a legal question and partially up to the creators, I think. Okay. So there's a potential world where one of these tools seems to have violated copyright and you might ban creators from uploading music that have used that tool. we're already taking if we get we have detection systems for if you if you are um if it's a derivative work of of something that already exists so we have systems to take these down uh if you're creating something completely new that isn't a derivative of anything there isn't that there isn't a copyright infringement then the labels tell us so so that's the other question on like what are these models trained on and we're not creating this model so so we're watching what happens there and we're going to follow the law but i think from a high level this should be a very exciting tool for creators for for musicians for authors for podcasters i i think i think if you look at something like notebook lm for example it's actually created by a journalist and a writer as a tool so i i think my bet is that these are bicycles for the mind but sort of bicycles for the mind on steroids right and that when those shifts happens there is always tension between the the people who didn't use these tools it feels like this is a little bit like cheating and the people are saying like, no, I want to be creative too.

11:14And it's always a different, difficult transition period. It's just the story of technology. And by the way, we're going to get to Notebook LM in a bit. So I definitely want to hear your perspective on that. But let me ask this one. So first of all, what you're describing is just sort of like, this is what happens in tech companies. You think you have something figured out. And then next thing you know, new innovation, you have to account for it. It's kind of what makes it exciting. It's what makes it fun. That it happens. And you already have addressed where this is going, which is, do we get to a place where, remember, you started talking about this saying we never could have anticipated that this is possible.

11:51And now it's like, feels like magic prompt and you get a song out. And I called them great earlier. They're not great, but they're good enough. And this is literally first generation of this stuff. It's going to get better. and as you think deeper about it do we go to a place where you can start to prompt music that is going to be better than any song that you might listen to that has been created for certain moods for instance like let's say you're in like a introspective mood or in a loving mood or in an angry mood and you're just able to prompt it and create that song that perfectly touches the heart at that moment and i started off talking about how this this format is beloved music is beloved it touches the heart and if ai can do that does that become the future of music so you've already said you don't want to play in it but is that something that you can discount from coming in so i think two things um music is used for many different things right um and so you have for example music that you're using to study i think is a good example the extreme version of that is people listen to white noise.

12:59So like, would white noise be generated? It's actually already artificially generated. It's one of the top podcast formats on Spotify. Exactly, right. So there's a scale here. And I think you're right. For certain things, maybe you could create better white noise. Maybe you could create better, you know, always varying ambient music for your studying. Maybe for gaming, maybe that music should automatically adjust to what's happening on the screen. So I think we're going to see lots of AI generated music for those use cases. but there's another use case for that which i think is very important a lot of people use music to build their identity right especially when you're a teenager you go to a concert you buy the jacket from that concert why did why did you buy that jacket well it's it's a it's a it's like a pin you're identifying with this band you're building your own identity through this band i don't think that will work with ai generated music because there is no one behind it so i I think some music, and I'm sure this is happening already.

13:54I'm sure many publishers are generating music for coffee tables and so forth. That will probably happen. But I do think the human need for having someone to believe in, an actual artist that you care about, I don't think Taylor Swift will be replaced by an AI. Not because the music couldn't sound similar, but because the whole point is Taylor Swift and belonging to something. So I think it's not a binary answer. Is this going to happen or not? know it's gonna not gonna happen i think both both will probably happen you know two years ago i might have fully agreed with you that there's always going to be that need for the story and the human connection and now i'm not so sure because because i do think that that this stuff can be good enough it's already proven that it's it it's already exceeded some of our greatest expectations and um i think we would like to think that we want that connection with the human but all right let's go right into notebook lm but but i think yeah one thing to say that i think is interesting is what tends to happen in these worlds is that the thing that is scarce gets even more valuable so one bet would be that true human connection gets more valuable than ever when a lot of what you talk to in the future may be llms that that would be my bet i'm hoping that's the case because part of the business that I'm running is predicated on the idea of connecting to a human who can sort of dissect and break stuff down is valuable.

15:22So I'm hoping that is the case. But I also, I'm not as sure as I used to be. And I think it's wise to not be sure of anything right now, given the pace of progress. And I think that brings us right into Notebook LM, which I was planning to leave for later, but you set it up perfectly. And it's this Google product that you can put notes in and then it will actually generate this podcast uh with two co-hosts that sound like ridiculously human yeah they don't they don't sound like robots and in fact people have sort of like uh fed them scripts where they like realize that they're actually not real people and they're ais and they just have this kind of breakdown and it's insanely entertaining but the bottom line is they're not quite where they need to be they're still a little hokey I think, and just kind of, they're like, if you listen for a minute, you're blown away.

16:12If you listen for five minutes, you start to cringe. But they also do a good enough job of breaking things down where they can pass. And I started to see them right now showing up in the second half of episodes where people are like, we're going to do the episode. And in the second half, we're going to give you the AI to listen to. But what happens if they end up being the first half? And Spotify has made a big move into podcasts. What do you think about the rise of these AI podcast hosts? So I think Notebook LM is very impressive. And you could predict, given the evolution of voice quality of these things and understanding of a language model, that this would happen.

16:51So I'm not at all surprised in a sense that you can generate audio that is engaging to listen to talk audio. But what I think was the great innovation of Notebook LM was that people generated monologues. And what humans really respond to are dialogues. And in retrospect, it's pretty obvious, like almost all podcasts are dialogues. Like if I sat here for one hour, it's not that interesting. So I think the big hack was to go through a piece of material and present it as a dialogue and prompt it the right way. There was also obviously, you know, the internal Gemini model at Google that is probably very good.

17:26and the voice models got better but i actually think what they found was product market fit for the actual audio format and it turned out to be the podcast format quite quite literally it's pretty crazy i mean somebody on threads tagged me and was like the male voice sounds like you and i listened and i was like not the same tone but also the cadence and the type of questions i'm like does that mean that i'm just like the blend of of all different i like this like you know kind of um the unremarkable middle of this? Or do they copy my voice? I'm hoping it's the second one. It'll be interesting to see if people either get tired of hearing the same two people talk about everything or the opposite.

18:05They get used to the same two people and would prefer to hear the same two people and build trust. I don't know. I think humans are very quick and prone to sort of anthropomorphize and it's sort of a hack on our human brain. So you feel like you know these people because you heard them talk about so many things now. so I think it's very interesting it's hard to predict where we'll go as a platform we view it the same way of course people are uploading these podcasts to Spotify as well and I don't know from the top of my head how you know if anyone has super high engagement but certainly people are are listening to them so it's the same question does this turn into a tool for creative people who can write stories but don't want to have the podcast around it or or just have no one interviewing them so they just do an interview around their own material I don't think I think you're going to run into the same problem where if you just ask it to talk about something it's not going to be very good you need a good source material so it's the same question is this a tool for creative people to get even more productive and creative or is it replacement of creative people my bet is it's another tool it's pretty interesting because it sort of broadens out the long tail and for those not familiar with the industry jargon it's basically just that like a lot of listening is concentrated in a small amount of shows yeah and there's this great long tail right like if you think about like a bar chart as it just sweeps out and there's uh lots of you know seldomly listened to shows yeah and the thing about these podcast generators notebook lm in particular is you can take it and create a podcast for something that's so niche that you would never have a show similar with ai code right you can start coding things i think you spoke about this in your interview with tomah cohn yeah uh on building one another linkedin podcast network show where now you'll code things that you would never code before because you can do it and it's similar it might go the same way with podcasts where you can for instance when i before i was uh heading down to manlo park to interview andrew bosworth i just dumped in all my source material and it read me a created a podcast about like his current statements there was like seven interviews that him and Zuck did before I showed up there and I was able to get the summary.

20:20That podcast never would have actually made sense to produce. But for me, it made sense. And maybe that's where this goes. Yeah, I love that framing. Like one useful framing, I think, of these techniques is financial framing. Like the cost of something goes to zero, like the cost of writing code goes to zero. Cost of doing a podcast goes to zero. Cost of prediction goes to zero. What happens? You know, and usually what happens is is the the alternatives to that good. they get challenged but the compliments to that good you know you have the famous like what if the the the uh price of coffee goes to zero then then the tea is going to be replaced but sugar is a compliment is going to explode so i like that way of of thinking about it and and i think what's going to happen is exactly what you're saying we're going to have enormous amounts of content around niches where it didn't make sense to produce a podcast so one way to think about it is just like the cost went to zero so i do think that the catalog is going to explode and then what does that mean well it probably means that the recommendation problem becomes even more important because now it's even harder to keep track of everything that is uploaded i also think that if you have this like vast sea of the perfect sort of discussion around any topic uh so the recommendation problem becomes more valuable to solve the bigger the the catalog is but i also think you're going to see the same thing as we see in music the superstars will actually also get bigger this is what i find fascinating people say like are you know netflix winning or youtube well the truth is both the tail is getting bigger but the shows are getting bigger and they're saying saying are they in this winning or taylor swift well both in this are winning but taylor swift is bigger than ever i tend to see like these both things happening at the same time which is why i'm hesitant to like say like that is going to happen right but not this yep okay let's talk about AI recommendation.

22:10It's a big part of Spotify and we're going to just start at the end for this conversation because your vision eventually is, so right now, like we'll go into Spotify, there'll be some algorithmic recommendation. There'll be some stuff that we listen to. Your vision, if I have it right, is eventually you want Spotify to be sort of this ambient friend for us that knows this context of the situations we're in, maybe AR. We're just talking about orion glasses before we start uh recording but maybe they know the context of where we are and can chime in and give us you know an example of type of some music that we might want to listen to is that right why would we why would uh why would you be pursuing that well i i do think of so when we um started spotify i was not part of funding spotify joined in 2008 late 2008 2009 Spotify was found in 2006.

23:00It was pretty early on. And it's interesting that this was before machine learning became a thing. And so Spotify was quite focused on social features for purposes of recommendation. We needed social features because that's how most people discover music, through a friend. So we wanted to connect to people. And then AI came along, or what was called machine learning back then. And we realized that through all the playlisting data we had, which is basically when we think about the playlisting data is almost as labeling for the user they are creating a set for themselves for spotify they were saying like these tracks go well together these tracks go well together so we got a lot of label data basically and we said internally now some people have a musical friend that happens to know their taste and so forth but most people don't so now we can build this friend for for everyone that was the ai but the interesting thing is like that thing of like building a friend for everyone that can give music recommendations like discover weekly it was always an analogy people did not think of discover weekly as a thought of as a set as a service and so forth i think what's happening now with ai is that the analogy is actually becoming reality and so you can see you can see us moving a little bit in that direction you have the ai dj that starts to give spotify voice that talks to you um and i think what is going to happen with these llms is at least for some brands you will start having literal relationships with them and i would love if it is the case that you think of spotify as actually a friend not an analogy anymore but reality this is a person that this is a thing that knows me well this is a musical intelligence a podcast intelligence a book intelligence and actually like hearing it you know tell me about new things and suggest things i'm interested in so i think that's that is where we're moving i think other brands are moving there as well i think if you if you look at some someone like uh duolingo they've actually only communicated through four characters all along when you get a push note if it's not from duolingo it's from lily or star or something they really they uh they give me a hard time if i'm away for a couple hours and that was also kind of an analogy but now with ai you can actually talk to these characters so I think this is a journey many companies are on.

25:14And it's interesting to play that out. It means that part of what was called branding before is like, what personality do you want your company to have? Not as an analogy, but literally. What personality should Spotify have? I think that's a fascinating time to work in tech. And it's something we're thinking a lot about. And I think that you might be underrating how much people view Discover Weekly as a friend. Now for folks who don't use Spotify, Discover Weekly will basically take into account your listening and your preferences and give you a playlist of what, 30 songs on a Monday morning. And they're just new songs for you to discover.

25:47And people will be like, Discover Weekly really got me this week or Discover Weekly is inflecting some pain on me this week or what happened. I thought we had a close relationship and now you don't owe me at all. And you also have, so you have this AI DJ. You can find it in the app. It's okay. I think there's definite, I'm curious, the feedback I've heard is people were excited about it initially and have moved away from it. And what is, so now I'm sitting in front of the person running product at Spotify. What is actually happening with this AI DJ? Is the experience there and are people using it?

26:23Yeah. So in the numbers, they're not moving away from it. It's actually very successful. So my friends are just pretty snobby music listeners. Well, for the people that use it, it's actually their biggest set. It's bigger than their Discover Weekly usage. So it's quite a binary experience. I think it's for people who don't know what they want to listen to and just want to put something on. It's working very, very well. What I would say, though, is when we launched the AI DJ, the big innovation there was that we managed to basically digitize the voice of a real person to make it sound very believable.

26:57But the things that it said around the music were, like, to some extent, heuristics and kind of repetitive after a while. So what we've done since then is we've invested quite a lot in, this is quite recent that is rolling out, in LLMs that actually tell interesting stories about the music. And we see very strong effects on this, on the retention of the application. So whereas the thing used to say, here's this and this song from this and that, I think you'll like it. Now I can say things like, this artist was just in Copenhagen or has played here and here the last week. Okay, I have to re-engage.

27:30You're starting to get interesting stories. You're starting to feel more personal. the other thing that i think is missing that i hope we can do someday is it can talk to you and you can talk back by skipping but obviously in the in the age of like talking to machines you would like to be able to just talk to it and say like no this was not very good my discover weekly this week was not what i wanted and give actual feedback and that is technically very possible now with these llms so so that's what i'm hoping will happen this should not be a one-way relationship which Spotify has been for technical reasons, it should turn into a two-way relationship.

28:06Okay. I have questions about that coming up. And to introduce that segment, I want to talk to you a little bit about how much we should allow the algorithms to dictate what our music experience and podcast experience is going to be versus how much should be dictated by us. How much agency should we have of our own choices? is Kyle Chica, New Yorker reporter, recently wrote about how he's leaving Spotify. I'm just going to put the argument out there and hear what you think. And I'll just read it straight from the story. He goes, through Spotify, I can browse many decades of published music more or less instantly.

28:44I can freely sample the work of new musicians. It has become aggravatingly difficult to find what I want to listen to. With a recent product update, he says, it became clearer than ever. what the app has been pushing me to do, listen to what it suggests, not choose my music on my own. What do you think about that argument? Well, I think this is an individual feedback, but I think generally you have very different types of users. So I'm going to get this person back on Spotify 100%. I think there's an interesting trade-off here that is real. So people want less friction. They want to spend less time searching.

29:25You want to make things as easy as possible, right? But there is this end of the line where you sit there and you just receive. You're kind of force fed and you don't give any signal back. Maybe a few clicks and so forth. And that's something that we want to avoid. I think this is where the industry is going. It's going more towards distraction content and sort of just sitting and receiving. And it's a little bit of a dystopian end of the line there. So what is interesting with Spotify, which we are reemphasizing, is that it was actually a platform where you invested quite a lot in your own playlisting, right?

29:59And there's a trade-off here between you could have a vision is we should be so good at machine learning that you should never playlist again. That would be the goal. Because then you've done the user a great service, supposedly. But then you also receive no signal and the user does no investment. So we're actually re-emphasizing playlisting quite a lot. Okay. Your own investment. And over the years, we've gone more towards machine learning and algorithms because it works. People listen more and they appreciate the service more. But we need to cater to everyone, including this reporter. So the Spotify user base is divided into many different kinds of people.

30:38You have the track listeners only listen to playlists. You have the hardcore album listeners. It's like, I just want to listen to an album the way the creator thought about it. I don't want to have the songs in between. um you have like the artists radio listeners only listen to to one one type of artist and it's a it's actually a big challenge to build a service that serves everyone when people are very different so we we try our best to make sure that the sort of music aficionados who want their library to be album album album can have their service and then but then you have the other people who just want like i just want my daily mix to play in my air i don't you know i just want to collect tracks they also need to be successful so we're trying to build and cater for both you can never please everyone 100 but we're trying to be statistical about it to make sure that it is uh it is uh vastly better for the majority of people but our goal is to cater to everyone and i do think there's a real point around going to zero user investment seems good in the short term but i don't think it's good in the long term because you actually lose signal from that user and at the end i think they feel less participatory in the experience even if the engagement looks high if you've done no feedback i don't know how much you feel this is actually your service definitely and look i'll confirm that spotify does listen to user feedback i sent a tweet out uh a couple years ago talking about how sometimes I'm baffled by the Spotify product decisions.

32:11And maybe it was because I was a reporter, but someone from your team reached out and I talked about how I wanted to see recently played. Oftentimes I'll be listening to something and then I'll go away from it and I can't find it in the app. And then a couple months later, there's a recently played button in the app. There are some great updates coming for you as well on that topic because this is a big user need. Maybe it takes a little bit longer than we want, but obviously our goal is to is to listen to user feedback and try to but we get very sometimes really completely opposing user feedback that's the tricky thing who do you listen to the most people who want this desperately or hate this desperately and there's a lot of both types of feedback so it's product development at this scale is sort of a statistical experience but you still have to have a bit of an opinion if you only treat us statistics the application is going to be very weird at the end of the day.

33:02So you have to combine some sort of vision and conviction, but you have to be still very data-driven. I think an interesting example of user investment and AI that we launched recently is something called AI Playlisting. So this is, I think, a good example of the first time you can talk to Spotify. So the AI DJ talks to you and it's getting better, but it doesn't listen. It listens to clicks maybe. But with AI playlisting, we built this experience where you can prompt what is an LLM with what kind of playlist. So we have an LLM and the LLMs have a set of world knowledge about music but then we have the music catalog and we have your listening history.

33:42So this is an LLM that understands your particular taste and you can ask it for a playlist with big drops and EDM for driving fast at night or something. And then it will try to do that And then you can say like, no, a bit more upbeat or not that artist and so forth. And this, I think, is a good mix of using AI, but not to force feed you stuff. It's actually very high signal. You are literally telling us what you want. And then when we say, here it is, you say that one, yes, no, no, yes. And then you can reprompt. So it's back to, I think it should be a two way conversation. And I think the first wave of machine learning allowed us to do the one way push.

34:22the next wave generative allows us to actually listen to you even in clear text so communicating with spotify just through skip buttons it's a pretty narrow signal so it's kind of hard for us to understand like when you skip it was it because you hated it or because you liked it but it was too many times now you can actually say like i really don't like this because like remove it so i was dming with kyle last night as like hey i'm gonna meet with gustav what should i ask him and one of the things he said is uh should spotify users be able to tweak the recommendation and your answer here is resounding yes.