Music consumers are becoming the creators with Suno CEO Mikey Shulman

**Sarah** (0:06)
Hi, listeners, and welcome to No Priors. Today, we're talking to Mikey Shulman, the co-founder and CEO of Suno, an AI music generation tool, trying to democratize music-making. Users can make a song complete with lyrics just by entering a text prompt. For example, I was playing with it this morning, and you guys all get to hear.
Feeling really excited about quality here for a company that is just under two years old, but is making waves in the AI music industries. Since you came out of stealth mode late last year, Mikey?

**Mikey Shulman** (0:52)
That's right.

**Sarah** (0:53)
Well, we're excited to talk to you about AI music models and how it's been going since launch.
Thanks so much for doing this. Welcome.

**Mikey Shulman** (1:00)
Thank you. I'm super excited to be here.

**Sarah** (1:03)
Okay. Maybe just start us off with a little bit of background. You're a kid who loved music, playing in bands.
How do you go from that to Harvard Physics PhD, building a couple of AI companies?

**Mikey Shulman** (1:16)
Yeah, I guess a bit of a circuitous route.
I've been playing music for a really long time since I started playing piano when I was four. I played in a lot of bands in high school and college growing up. And the dirty secret is I'm not that good. And so the smart move, I suppose, for me was to pursue the thing that I was relatively better at, which was physics. I went to college and then to grad school and did a PhD in physics.
Studied quantum computing. Maybe for your next podcast, I can tell you about why you shouldn't go into quantum computing.

**Sarah** (1:51)
What did you think you were going to do? Like, did you think you were going to be like a theoretical physicist or like an academic?

**Mikey Shulman** (1:57)
Oh, goodness. Well, two things. Like, I've never had a master plan, so I don't think I thought what I was going to do or not going to do. But I am certainly not great at physics. You know, I think I had a reasonably successful PhD, not because I'm good at physics. The quantum mechanics that I studied was worked out in like the 50s.
There was a lot of very tricky low-temperature microwave engineering that turns out to be really important for actually doing this stuff. I got lucky that I was relatively good at that compared to all the other physicists. So, you know, kind of something on the boundary between two disciplines.
I enjoyed every second of that. I would do it all again, even knowing what I would be when I grew up or when I grew out of that. Still very close with my PhD advisor. I still live a long distance from my old lab. You know, it's kind of a fun place to just walk around Cambridge, Massachusetts. But yeah, quantum computing is cool. Not what I wanted to do with my life. I found a company called Kentro by accident, not founded, found.
They were local and I met them and probably 10 people at the time. And I met all 10 and I really, really liked them. And I said, let's go do this. And I was hired as a software engineer. And I think I got really, really lucky in terms of timing. About a month after I joined, the machine learning opportunities came along. And in 2014, guy with PhD in physics is what passes for machine learning engineer. And so I took full advantage of that opportunity, learned a ton, got to build a team, got to build some fun products.
We were acquired by S&P Global in 2018 and got to pursue a lot of fun stuff after that acquisition as well. So I guess I found my way into AI somewhat by accident, but I really like it. It's a lot of fun.

**Sarah** (3:47)
So you guys actually started with this open source model, BARC. Can you talk about what the idea was at the very beginning and how you ended up in music generation?

**Mikey Shulman** (3:57)
We were doing all text at Kensho and we did our first audio project after we were acquired by S&P Global, which was learning to transcribe earnings calls. So I'm sure both of you have read an earnings call transcript.
Exceedingly likely, it was done by S&P Global. It used to be done completely manually, very painful, and we could lend a lot of speed and scale by bringing automation to that.
And we fell in love with doing audio AI. Like, we happened to be musicians, but it kind of took this very honestly non-sexy project of earnings call transcription to show us how much we loved it.