Suno's Mikey Shulman: Everyone Can Make Music Now

[00:00] Before Suno, basically... [00:01] Everybody was a consumer of music. [00:03] Compared to the 8 billion people on the planet, there are very few people who make music and the rest of us consume it. [00:09] The crazy thing about Suno is that on any given day, 90% of the users are going to create something. [00:14] And [00:14] The thing that's hard to wrap your head around is you're not creating it to go bring it elsewhere, by and large, to do something with it. People are creating music for the fun and enjoyment and fulfillment that comes with being creative. [00:26] That, the creation, is actually the entertaining bit. And that is the big step change. [00:31] Music. [00:48] I'm delighted to welcome Mikey Shulman. Mikey is founder and CEO of Suno, which is building a music company or a creative entertainment platform, and has been one of the most novel consumer applications I've seen out of AI. And I'm very, very excited to ask you about your journey and what's ahead for Suno. So thank you for joining us today. [01:07] Thank you for having me. I'm excited. [01:08] Okay, awesome. I want to start with your background because it is very, very unexpected. You went from a physics PhD at Harvard, I think quantum computing with solid state spins, to building the largest AI music company in the world. Like, [01:23] What insight connected those two things for you? [01:26] Uh... [01:27] You know, I don't know how, I don't know, like on paper, I guess I have no business building a consumer entertainment company, but...

[01:33] A lot of people went from [01:35] physics into AI, just like, you know, 30 years ago, a lot of people went from physics into quantitative trading. [01:41] Um, [01:42] I'll be honest though, I was an okay physicist only. [01:46] And there are a lot of better physicists, including one of my co-founders, [01:50] And I think what I mostly learned is [01:52] Playing at the nexus of two things. [01:55] that don't usually play together. [01:57] is just a massive opportunity in all domains. It can be music and technology, it can be [02:03] Uh, [02:03] quantum mechanics and low temperature microwave engineering or it could be whatever else you're going to do. [02:08] You and I got connected in the very early days of Suno. One of our mutual friends, Harrison Chase, was one of the earliest Suno Discord users and he was having far too much fun making songs in your Discord. Maybe tell us about the early days of Suno. How did it come together? Did you set out to build? [02:28] A music company? [02:30] So, [02:31] Originally, we thought this would actually be too hard. [02:34] And it's because [02:37] You have to rewind. This is like pre the chat GPT moment. [02:41] We did some like back of the envelope math [02:43] We knew we loved audio, but the back of the envelope math told us that actually producing good music, making good music, generating good music was like a couple of orders of magnitude. [02:54] away in terms of [02:56] compute and model size and capability [02:58] And it's because [03:01] music sound in general is like very unwieldy it's not in discrete bits like text is

[03:06] And [03:06] So we actually started building a company that was all around [03:09] using the same technologies to make sense [03:12] of audio [03:13] not to produce it. [03:14] And [03:15] Very happily, pretty early on, we had the right breakthroughs and we realized, oh, we actually can make music. You're pretty good at math. What did you get wrong with your back of the napkin math then? The math was right. We just had some breakthroughs that said like it's actually you don't need that amount of compute. You can make the right technological breakthroughs to make. [03:35] if you want to think about it, basically just compress audio really, really efficiently. [03:39] And that worked a hell of a lot better than we anticipated. So it was like a very nice being wrong moment. [03:46] Not all being wrong moments are so pleasant. And [03:49] To be clear, at the beginning, the music was terrible, but we still stayed up late. I thought it was good. He was one of your first 10 users, I think. He thought he was pretty good. [04:00] Certainly before we put it on Discord, the music was very terrible. Before we put it on Discord, we could make like 12 and a half second clips. [04:07] that wouldn't always listen to the words you ask them to sing. [04:12] But we had so much fun doing it. And we thought other people might have fun doing it. And so we kind of took the example of Midjourney and we said, [04:21] it's really easy to put a Discord bot out and see, will people enjoy it? And we put it out there, and a hell of a lot of people enjoyed it. And that was a really confirmatory moment for us. And so a lot of people told us not to build a music company, [04:34] It's not the easiest business to work in. Speech is really big. There's a lot of great

[04:38] Um... [04:39] business use cases for building speech technologies. But when you are staying up late playing with the thing, [04:44] and you don't want to go to sleep, it's like a really good sign that that is what you are meant to be doing. [04:48] And so... [04:49] That's what we did. [04:50] I love that. Are you a musician? [04:52] I am. I play almost every day. I grew up playing a lot of piano and ended up picking up a bass around age 12 and playing a lot. [05:03] A lot more of that. [05:04] Okay, so personal and passion point. That's awesome. You know, the revisionist history is that, which is true, is that we used to have jam sessions at our last company in one of my co-founder's basements. [05:14] And it's true. We had a lot of fun there. It's not why we started the company. Again, we thought it would be too hard to do this. It was just fun. [05:20] Meaning at Kensho? At Kensho, yes. Where I met the great Harrison Chase. [05:24] The Kensho Mafia is like pretty unparalleled. There's Harrison, there's also Daniel Nadler. [05:30] Sam Whitmore, you, there are a lot of you. There's a lot of us. I just credit Daniel with that. [05:36] Honestly, Daniel is like, I think the best. [05:40] object lesson in what talent density can do for a company. [05:43] And it was a lot of people with non-traditional backgrounds. It skewed very young. But he was great at finding people and great at convincing them to join. [05:50] I love that. Okay, so walk us through what happens when somebody types... [05:54] upbeat 90s hip hop track about a road trip. You get the prompt in, what happens? What is the modern model doing to be able to pass something back to the user that seems like it's quite special? [06:06] In some way, it's actually pretty simple.

[06:09] A prompt like that, you have to figure out what are the words of this song. [06:13] And we use various LLMs to do that, to make the lyrics. And [06:18] Um, [06:18] So it's taking basically the queue there is road trip. And so like, what should this road trip be about? And it will probably get it wrong because you didn't give us enough information, but that's actually okay. You can iterate on it. [06:28] and then you said 90s hip hop. [06:29] And we tried to expand that out into [06:32] a set of cues that the model can really understand. What is the genre? What is the style of this music? [06:37] And then you put those things together. You have a lot of lyrics. You have a lot of styles. [06:41] And we have our models that are trained to take in all of that information and just produce sound. [06:46] The amazing thing here is that the models don't know [06:49] that there's vocals and instruments. It doesn't know what kind of instruments there are. Very early on, it was actually-- [06:54] quite obvious to us that [06:56] The more musical knowledge we give the model, [06:59] the more constrained it will be in a bad way. [07:01] And so we actually just model everything as sound. [07:06] And that's what made it so hard, but ultimately that's what makes these things so powerful. So just to be concrete about it. [07:11] Um, [07:12] In Western music, there are 12 tones. If you tell the model there are 12 tones, it will only ever produce those 12 tones. You will be forever limited. And if you tell the model there's 200 instruments, [07:23] Those are the only sounds that you'll ever be able to make, and you won't get... [07:26] The next Skrillex using Suno. [07:28] And so [07:29] For us, it was all about let's throw away everything we know about music. [07:34] And let's try to do this from scratch. And it's like, it's just a sound wave. [07:38] It's just sampled at

[07:40] 48,000 times a second, and it is a continuous float 32 number, and let's figure out how to model that. [07:47] And that was a lot of the early breakthroughs that we had to make. But once we did, now you are only constrained by what you can describe and your imagination. [07:56] That's so cool. Have you found that we've basically just... [07:59] rediscovered, you know, the existing genres of music and the 12 notes and like, have you, I guess, independently seen just that that same behavior emerge when you're trying to, I guess, learn music from first principles? Or have you seen like a different set of capabilities emerge? [08:14] No, the amazing thing is now we see... [08:17] new things emerge that [08:19] you never would have thought of. And so most of the time, this looks like blending genres that really have no business going together. And so you'll get [08:27] I don't know, trap with a sitar in it. [08:29] or you'll get [08:30] Um, [08:31] country with 808s in it or whatever it is. And again, this is like really empowering people to do the things that are in their heads. And it's in a way that [08:39] would not have been possible without a technology like this or would have been really, really hard. [08:44] Um. [08:45] We see microtonal music. It is really inspiring to go and just look at all of the crazy things that people are making. [08:51] A lot of them sound like [08:53] genres you know and a ton of them sound like [08:56] Totally strange and bizarre and lovely. [08:58] That's awesome. That's really cool. Are there certain genres that you're finding your model is... [09:03] better at? [09:04] And certain genres were worse at? [09:06] Definitely. We are...

[09:10] I mean, I attempt not to say like good and bad about music other than, you know, it's sampled well, like the full bit depth or full sampling rate. [09:20] to the extent that you can make such generalizations. We're very good at country. We're very good at pop music. [09:26] And I think [09:29] The cartoon maybe to have in your head is that [09:32] there are some genres that are somewhat more formulaic than other genres. And so perhaps we're like... [09:39] better at those. [09:40] But I have some sneaking suspicion that for those, it's as much raising the floor as it is raising the ceiling. And for the things where we're less good at it, we've not raised the floor. And so we make a lot of bad music. But we have also raised the ceiling. And if you're willing to go for long enough, you'll find amazing stuff. That's so cool. Suno V5. Suno. [10:01] Seems like it was a real step change in quality. What goes into one of those step changes? [10:07] You know, it's really hard to predict when the step changes happen because it's really nonlinear in – [10:14] Both the research inputs [10:16] But actually, it's... [10:18] It's not even linear in how much our testing says the model is better. [10:23] And so just as an example, we can measure how much one model is preferred to another model. [10:29] and [10:30] you may come up with it's 10% preferred or 15% preferred. And you can take two different models and one is 10% preferred or 15% preferred. [10:37] um [10:38] And the uptake on the other end, how much our users actually love it and use it, or how much the product grows when you release it, won't necessarily be all that correlated with what the preference signal is. And it's because...

[10:50] music is messy and there's lots of other things that go into it. [10:53] But to take a huge step back, like we have a pretty aggressive research roadmap and [10:57] in some weird way, we're always working on this thing, you know, like we know what v6 and v7 are at some point. There's lots of things that you want to have your model do there's lots of improvements that you want to make. And [11:08] It's almost an arbitrary cutoff of saying like, okay, this is the break. This is what we're going to call V5.5. And everything that comes after is going to go into the next models. And almost just to keep it on a steady cadence of when we release things. Because what you would hate to have happen is we don't release stuff for like two years and we try to make the music model to save humanity. And that's going to come out in two years and we're going to do nothing before then. [11:32] Yeah, totally. How much of each of these improvements do you think is just a function of scale? [11:39] scaling compute, scaling data, and then getting a lot of human preference data back. How much are you guys doing, I guess, more novel research? [11:48] Music is really not a scale problem. The models are pretty small. [11:52] for a variety of reasons. [11:54] um [11:55] And I think people will often... [11:58] incorrectly take what they know from [12:00] LLM land where models are giant and scale helps a ton and apply it to music. I think the cartoon that I have in my head is that [12:07] in llm land there's all of these benchmarks and you can quibble about which ones are flawed and which ones are good [12:13] But these benchmarks exist, and scale is actually a pretty efficient way to climb up the ladder and just keep doing better and better on the benchmarks.

[12:21] In music, there are no right answers. There are no benchmarks. [12:24] And so scale is somewhat less helpful in solving it. It's a messier problem in many ways, aligning models to creative human tastes. You and I are not going to agree on every song. [12:35] You and I aren't even going to agree on how to describe it. I'll just defer to whatever you say. You have such a criticism. I mean, I don't think you want to do that. But so the and the models not being that big actually lets us [12:47] get you the music quicker, which turns out to be really important for [12:51] good UX. And so I think a lot of this [12:54] boils down to [12:56] Research. [12:57] um and preference data and so we gather preference data [13:01] that lets us align models to what our users like, [13:04] A really underappreciated thing is how much this preference data actually lets us do research. [13:08] Without the scale of preference data that we have, we wouldn't even be able to develop the techniques that we are using. There are really some virtuous cycles there in how the product itself, [13:20] keeps getting better just by virtue of having people use it. [13:23] Interesting. And I guess you can use [13:26] the human preference data in a much stronger way than the text models, because they're all worried about sycopancy, right? And for you, I guess that's much less of a challenge. 100%, 100%. And so I think, yeah, there's just a tremendous amount of edge comes from our ability to understand it, do research on it. [13:44] and then RL that back into our models. [13:46] That's awesome. Okay, I want to switch gears a little bit and talk about music as a consumer phenomenon. And, you know, you've mentioned consumer creative entertainment platform at the beginning, I want to dig into what that means. Maybe starting with like, seems like music is just like a cultural social phenomenon of, you know, I like this song, I send it to my friend, you know, it's a it's a scarce resource, we bond over liking that song and, you know,

[14:16] having the mixtapes, listening to it together, et cetera. And to me, music has always just been like this shared cultural experience. That's what it is. Do you agree with that? And then if so, what does AI music mean for that? [14:30] Um, [14:31] I agree with that very strongly. Music has a very different place and culture than other media. [14:35] in a variety of ways. [14:37] One is actually people's tastes are far more developed in music than they are in other media. Like everybody has taste in music. [14:43] in a way that most people don't have taste in film or literature. [14:46] And the other thing is that music is actually inherently a much more social medium. [14:50] And if you think about it, how [14:51] going to a concert, [14:53] is an inherently social thing, even though you're only really looking at the performers, and it's because of the people around you, in a way that... [14:59] let's say going to a movie in a movie theater isn't quite as elevated as it would be [15:03] compared to an empty movie theater, for example. [15:06] And so [15:07] I think this is actually largely that [15:11] Humans communicating sonically through our mouths and ears, and therefore music is like a much earlier method of communication than writing. [15:20] um it's like much more in our dna i think music compared to other things i'm obviously biased i obviously love music [15:27] Um, [15:28] I'm not sure. I think people assume that, oh, you're just going to have like AI powered Spotify and it's going to dehumanize it and. [15:35] music is going to get terrible. That seems to me to be obviously wrong. [15:39] I don't think you're going to make a better Spotify just by powering it with AI. [15:43] And the thing that's really interesting is actually how can we

[15:46] not just change, but elevate the place of music in culture. And music has this other funny thing that by virtue of being so ubiquitous, it ends up being in the background. [15:55] a lot. [15:56] And the thing that's amazing is that [15:58] AI can be used to actually change that to [16:01] augment how music is perceived in society and in culture, augment how it is used socially because it's actually become less social, [16:08] in the last 30 years. And so that is the corner of the universe that we play in and that we are really excited about. [16:14] Hmm. [16:15] Do you see yourselves as today, and I guess when you look at your users, are people more creators of music or are they more consumers of music or both? [16:25] This is the crazy thing about Suno. Before Suno, basically everybody was a consumer of music. [16:32] you know, compared to the 8 billion people on the planet, there are very few people who make music and the rest of us consume it. [16:37] And that's fine. It tends to cater to passivity. It tends to cater to... [16:43] making it less social and more impersonal. [16:45] and [16:46] The crazy thing about Suno is that on any given day, 90% of the users are going to create something. [16:51] And [16:52] The thing that's hard to wrap your head around is you're not creating it to go bring it elsewhere, by and large, to do something with it. [16:58] People are creating music for the fun and enjoyment and fulfillment. [17:01] that comes with being creative. [17:04] that the creation is actually the entertaining bit. And that is the big step change. It's like, [17:09] Everybody in the world is creative. [17:11] Being creative makes you feel a certain way. This is like in our DNA. And we are basically using technology to allow everybody to feel those warm and fuzzy feelings. A lot of like the inspiration for me personally for doing this comes from just remembering like the fondest memories that I've had or some of the fondest memories that I've ever had are making music with my friends.

[17:30] not even performing in bands. Like, practice was so much fun, and you get really close to people making music. And it's because [17:37] It feels really good to be productive. [17:39] in a way that [17:40] Um, [17:41] Doomscrolling your favorite app for an hour does not feel so good when you're done. [17:46] i was an orchestra kid so i was not doing nearly as cool music as you but i totally what did you play [17:51] Violin. [17:52] Do you still? [17:53] Yeah. Oh, excellent. [17:55] I have perfect pitch and I let's just say I'm definitely not playing 12 tones now. So my ears bleed when I play. But I totally agree with you. Okay, so it's like a self expression slash active entertainment platform, some parallels to gaming, and some parallels to even like cloud code, right? [18:16] Absolutely. So I think the thing that's amazing about making music is that [18:21] You feel good and fulfilled and you enjoy making it and then you listen to it. And there are parallels. And so that's what we call creative entertainment. The entertaining part is being creative. It's not that you are being creative for the sake of bringing the piece of content somewhere else. [18:36] Um, [18:37] I think you see that in... [18:39] um cooking people like to cook even though they can get a better meal at a restaurant and it's because [18:43] It is fun to cook and it is fun to consume what you make. [18:46] And I think a lot of what makes Cloud Code or any of the other platforms so special is that it's fun to build things and it's fun to use what you build and even. [18:55] though most of the things that I build are definitely not meant to be hosted in AWS and used by millions of people, I actually enjoy the act of building and I enjoy the act of using the thing that I built.

[19:06] I predict that like in 10 or 20 years, there will be way more of these creative entertainment things [19:12] all over the place. And it's because [19:15] That's actually finally possible. That is the thing that AI unlocks. It unlocks lots of intelligence things too, but it actually lets everybody be creative in almost any domain. [19:24] Yeah. [19:25] I'm guessing you have an opinion on this. What do you think of the word slop? [19:29] I do have an opinion. I actually, I mean, my answer is usually it's thrown around without any meaning. And I don't know what people... [19:39] what people mean by that. I made [19:41] Uh, [19:42] Two songs with my five-year-old yesterday. [19:45] is that slop in the sense that [19:47] 99.999% of the planet has no interest in hearing that. Sure. [19:51] But that's really meaningful to me. And so if you call that sloppy, I'm not sure I care. [19:56] It's an interesting question though, right? This has happened before, at least in music, where when way more people start to be able to produce something, people get afraid [20:06] that it's just going to flood all of our ears and all of the platforms with more content. [20:12] And [20:12] This happened when people started to be able to make music on their laptops. You had like a lot of 13 year olds making beats in their bedrooms. And you fast forward to today, that seems like obviously a good thing. Yeah, there's way more music. [20:24] It means that there's way more quote unquote bad music. [20:27] But it also means that there's way more great music, and there's new kinds of music that get made, and there's new kinds of stars that get made. [20:34] I see no reason why way more people making music again would be any different from that.

[20:41] I love that. [20:42] So we talked about the floor, the slop floor, the non-slop floor. What about the ceiling? Tell us a little bit about the most incredible things people have been able to do with Suno. And I think you guys have had some chart-topping hits now. Maybe talk a little bit about that. [20:58] Um, we have had some chart topping hits. We've had people sign to record deals. We've had people make single songs that chart. [21:05] Um, [21:06] And that's amazing. And I think about that as that is a... [21:09] New Creator, [21:11] coming with a new perspective that resonates very strongly with people. And so that is obviously the ceiling going up. [21:17] My favorite example is Zanaia Monet. [21:19] who it's the stage name of [21:22] a poet [21:23] who took all of her beautiful poetry that she had been writing for like a decade and started to make music out of it, [21:29] and found an entirely new voice and an entirely new audience to resonate with her art. And, like, yeah, I think this is fantastic. This is, this is, [21:37] Um, [21:38] people connecting right these are this is like the the most personal thing in the world and when you go listen to the music you'll realize it's extremely personal like the best music will always require human guidance and it's because music again music has no right answer you [21:51] like a piece of music because of how it sounds, and because of the messenger who delivers it. And we will find new messengers with new sounds, and we already are. And that to me, it's like obviously the ceiling is going up there. [22:03] The other thing that's really cool is even if [22:05] I just know that there are tons of charting tracks that have little bits of Suno in them. They're not entirely Suno. And it's because...

[22:12] For the professionals, it's also just an amazing tool to use as part of your workflow. It's not your whole workflow. And so there's this weird thing where I think people incorrectly say it's like either all AI or non-AI. And... [22:25] the vast majority of music will have some AI in it, just like the vast majority of music today is auto tuned. [22:30] or is digitally produced. And again, more tools let you push music forward faster, let you find new sounds faster. To me, this is like obviously the ceiling going higher. [22:42] That's amazing. [22:43] I [22:44] Okay, so you chose to go after music, which is like probably the one industry that a lawyer would tell you not to go after. Because the minute you're there, you have pitchforks coming after you. I think you just had a pretty landmark settlement partnership with Werner. Can you tell us more about that? [23:03] what you think that means for the future of collaboration with the existing professional music industry. [23:08] Absolutely. I think just to back up, you know, [23:13] I think people incorrectly assume that [23:17] We hate the existing music industry, and especially we hate the record labels. People also expect me to say, like, oh, the record labels are cooked. [23:24] I think that's obviously wrong. [23:26] they're some of the most culturally important institutions in the world. [23:29] They understand music and they understand music culture. [23:33] they cultivate and grow stars that resonate with billions of people. And [23:39] The way I see it, it would be a real shame if there were two worlds of music, if there were like an AI world of music and a non-AI world of music.

[23:45] One is it makes no sense because most music will have some AI in it. [23:48] But the other is it's just bad for the end user. [23:51] to think about having to separate [23:53] these things in your head and to have to go to different platforms to have effectively similar [23:58] Um. [23:59] usage patterns or interactions. And so what I'm most excited about doing with Warner [24:04] is actually building things together that could never have existed before and building products that let [24:09] fans interact with their favorite artist and the [24:12] really deepen [24:14] the artist-fan connection in ways that are just positive, some for everyone. It's great for the artists. They get to engage with their fans. It's great for the fans. They get to feel like they're engaging with their favorite artists through music. It's great for the rights holders. Obviously, this is like a heavily monetizable thing. [24:30] And it's something that literally could not have existed up until like approximately right now. And my sincere hope is that going forward, we find way more of these opportunities of things to build together together. [24:40] that couldn't have existed until today. And just to say it out loud, like... [24:44] the digital musical experience has basically not changed [24:48] for 25 years. We've just been streaming music for 25 years. [24:51] And, um, [24:53] I think music is like, do. [24:55] for a new innovation and a new format. And so that's what we're here to do. [24:59] When are we going to see Suno at Coachella? [25:01] you probably have already it's probably in a lot of the music it's probably in a lot of the backing tracks but I mean like a main stage like a consumer participation thing I hope that at some point in the next year

[25:17] we see a truly interactive concert. [25:19] where the audience is actually able to participate [25:21] and make music with that artist. [25:24] One of the coolest parts of my job is if I go and I demo, [25:27] pseudo to an audience of hundreds or even a thousand people is making a song with that many people all at once. [25:33] And it's a very special moment. It's like almost religious, you know, like a lot of religions will do like chanting and singing in large groups. And... [25:41] why does that have to be confined only to a religious context? Why can't that happen at Coachella where people are already so [25:48] excited about being together at a festival. And so my sincere hope is that happens in the next 12 months. [25:54] Love it. Okay, we talked a lot about the model layer and then the... [26:00] I guess the [26:02] cultural experience of making music. I'd love to talk about the application layer product building because I think that's also an area where you guys have been really innovative. What's your approach to how to think about building in the application layer? [26:17] I guess a lot to say here. The first thing is actually... [26:20] There isn't enough innovation for consumers right now. [26:24] But the average consumer is not willing to put up with rough edges, and it's because... [26:28] You're not using this for work. You're using this for fun. [26:31] you're probably paying for it and not your boss is paying for it or your company is paying for it. And so there just needs to be a bigger emphasis on, [26:39] Um, [26:39] the actual experience that we deliver to people. [26:42] Also, just if we're being honest, like, [26:45] It's unclear how much moat exists in only a model.

[26:48] And it's like, I'll just say it, like Google has started to build music models. And while ours are way better today, [26:54] They're Google and they'll outspend us seven days a week and [26:57] they can probably catch up on the model side. And so I think it's just really undervalued to invest in the product and the UI and the UX to make sure that you're constantly delighting people. [27:07] Um, [27:09] you know, [27:09] One of our company values is actually like we're just a music company. [27:13] And in many ways, I don't think of us as a technology company. [27:17] This is to make sure that we're not building technology for the sake of building technology. We're building technology for the sake of delighting people. [27:24] And infusing that in the culture is actually just like [27:27] really helpful in getting people to realize what the whole point of the company is. And so that manifests itself in lots of little ways. [27:34] But from a product building strategy, that's what it is. [27:36] Thank you. [27:37] That's awesome. What are some of the, I guess, consumer product decisions you've made that you're most proud of or that were the most contrarian? A bunch. One that I got wrong was getting off discard very quickly. [27:50] I thought we would be on Discord for a while. We got off Discord at the end of 2023. [27:57] And we released a pretty thin, not full-featured web app [28:01] And it took five days for 90% of the traffic to move to the web. So it's just like an overwhelming signal that I had gotten that wrong. [28:09] Maybe the biggest one. [28:10] and the most contrarian one is at the time a lot of people were experimenting [28:15] with music. [28:16] Let me give two actually one was to focus on songs and not just background music to focus on lyrical music and

[28:22] And it's because a song is a story. [28:25] and captivates you in a way that vocalist background music just won't. [28:30] It was also just way harder. [28:31] And so nobody was really able to do that at the time. And so by figuring that out, that was certainly a source of moat. [28:38] But in hindsight, it's not just that we were able to do something hard. It's that the human voice touches people in a certain way and just makes the product way more delightful than just making background music for fun. And then the others also in the same direction. [28:50] We decided to make full songs. [28:52] And so again, a song is a story. [28:54] You know, it's maybe on average three or three and a half minutes. And we optimized for that, even though originally, you know, [29:00] Most technologies just let you make something like 10 or 12 seconds of music. [29:03] at the expense, [29:05] of sound quality. [29:06] And for the longest time, [29:08] our audio is really not crisp. And every single one of our competitors had just way crisper audio. And everybody could hear one second of a Suno song and know, oh, that sounds like crap. That's a Suno song. And to just go all in on that and say like, [29:22] Okay, we're going to make full songs, and yes, they're not going to sound amazing, but they are still going to tell the story. [29:27] instead of making perfectly sounding audio that just is like background music. So the choice of technologies there was to use autoregression instead of diffusion, but it was really product-driven. [29:38] And to say like, it's not just that we like auto regression because we have [29:41] Like, [29:42] emotional attachment to that technology. It's because we think that making a song and telling a story is more important than making crisp audio. [29:50] Hmm. [29:51] That's so cool. What's ahead for Suno?

[29:54] 300 million in revenue run rates. I mean, you've made it extraordinarily far. What's ahead? [30:00] A lot. I think it's really early. Most people don't even know about us. [30:05] The product is still very crude. [30:07] There's a lot of room to run. I think you'll see us do a couple of things. [30:10] One has tried to increasingly make it a more social interaction. [30:13] like music is meant to be social. And so you are meant to be sharing music more with people, but also creating more with people. And that can be both synchronous and asynchronous. And so [30:24] Perhaps one day I'm going to share you not even a song, but a template for a song that you are going to explicitly riff on. [30:30] and sent back to me, and that is you and I kind of co-creating. Maybe you're going to do that with your favorite artist. [30:34] with some of their old music that never got released, whatever that may be. And... [30:39] I think you will see us go [30:41] Um... [30:42] Much more. [30:43] in the direction of letting people express themselves in the music. And so like the last big feature we've released is the ability to use your own voice [30:51] when you hear yourself in the song, [30:53] you get so much more attached to it. [30:55] But actually even more so is when I send you a song [30:57] And you can hear me in it. [30:59] that song will resonate much more than some nondescript voice, even if that nondescript voice is very good. And it's because the human ear is highly attuned [31:06] to voices. [31:08] We kind of felt that way. [31:09] Um, [31:10] Both of those, being more social and letting people pour themselves into the music. [31:14] Um, [31:15] will be a huge focus for us for the next 12 months. [31:17] I love that. We love music videos. [31:19] I love music videos. I don't see enough music videos getting made. I grew up watching music videos like on MTV. Yeah, me too.

[31:29] There's just a huge difference between a music video, which... [31:32] is heightening the song and telling the story [31:34] versus background music to put [31:37] behind whatever YouTube content that I may make. And I love the former, and I'm much less into the latter. And it's because what we would like to do is pull people into music more than they are now and not just have music be forever a background thing. There's actually a video product in beta in Zuno right now. And so people really love it. [31:57] Nice. Um. [31:58] That's really cool. I can't wait. Why do you think? [32:02] There's so few consumer... [32:04] founders in AI right now. Like what's up with that? Everyone's, everyone's willing for the enterprise. Like OpenAI just shut down Sora, which to me was [32:13] you know, [32:14] I mean, I understand the reasons, but why do you think there's so few people building in consumer right now? [32:19] I mean, I should ask you that. You're the professional investor. I mean, my theory is like, it's just harder and harder. [32:26] There are a lot of obvious business problems to solve. [32:29] Um, [32:29] And, uh, [32:31] I'm, you know, like, I'm happy. I'm happy to have less competition, honestly. Why do you think it is? [32:38] I think it's very clear to see how AI is going to automate a lot of existing business processes. [32:45] I think it takes real creativity. [32:47] to dream about how AI can seep into [32:53] the way that we actually play and create. I think it takes real creativity to see that. And most people, when they think AI music, probably think AI Spotify, which

[33:04] just sounds terrible. And, and I think it takes a lot of creativity to [33:09] to do what you're doing. [33:11] Well, thank you. Yeah, I think like... [33:14] We are much [33:15] more inspired and motivated. [33:18] by doing something that wasn't possible until today instead of [33:21] automating or speeding up something that already exists. Again, there's a lot of business value in automating and speeding up something that exists. [33:30] In some sense, it is just more fun to do something that could never have... [33:33] been done before. [33:34] Yeah. And like, what are we going to do with all our time after, after all the robots are doing all the work? [33:40] You're not going to want to do school for now. You're going to want to be, you're going to want to be productive and fulfilled. [33:44] Yeah, exactly. Awesome. Mikey, thank you for sharing everything about your journey to Suno has been so cool. And to see you at the helm of a music company and an active entertainment platform and just, you know, defining what the creator layer means in the world of AI. It's been extraordinary to watch your journey since the original days of, you know, Harrison and your Discord. And so kudos on what you've done. Big admirer of you and Suno. [34:14] Thank you so much. This was a lot of fun. [34:17] *music*

[34:41] Thank you.