The Ledger
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Shulman: Suno does not only train its models on music
“People are always surprised to learn that we don't only train on music.”
Shulman: Suno prohibits users from generating songs using copyrighted lyrics
“We actually don't let you do that. And it's because if you're taking someone else's lyrics, you didn't own those. You don't have the publishing rights to those. You can't remake that song.”
Bubna: Modal's Biggest Use Case and Initial PMF Was Custom Non-LLM Inference
“Our biggest use case actually is elastic inference. And the thing we first found product market fit with was inference for custom models. So we kind of stayed away from the LM space and we were serving companies like Suno for audio, Runway for video, robotics …”
Modal CTO: Suno runs 100% of inference on Modal
“They use modal for all their inference, and that's because they have like a custom, they have completely custom model architecture, and that means that they have to be at the code level and tweak things that are not Yeah, it's an API.”
Swyx: Suno grew from zero to $20M ARR running on Modal
“Suno ramp has rated as one of the top ranked fastest growing startups of the year. I think the last public number is like zero to twenty million this year in ARR and Suno runs on Moto. So Suno itself is not GPU rich, but they're just doing the training on, on …”
Shulman: Repeating prompt keywords too often degrades music model outputs
“It's actually, you can't really repeat too many times. You kind of, it gets like the hypothesis gets like a little too out of domain.”
Shulman: Suno aims to undo cultural barriers preventing people from making music
“There's actually a lot of cultural forces that kind of cue you to not think to make music and that's kind of what we're trying to undo.”
Streaming throughput constraints prevent Suno from scaling to 175 billion parameters
“We care a lot about how many tokens per second we can generate because we need to stream new music as fast as you can listen to it. And so that is a big one that I think probably has us never get to a hundred seventy-five billion parameter model, if I'm being …”
Suno avoids hardcoding musical rules into its generative models
“We try not to impose anything about music or audio in general into the model, and we kind of let the models learn things by themselves.”
Shulman: Suno restricts prompts to prevent artist impersonation
“We try to be very careful not letting you impersonate, and it is possible.”
Shulman: Bark was the first open-source transformer-based TTS model
“As far as I know there was no other certainly not in the open source text to speech that was kind of transformer based.”
Shulman: Professional musicians are using Suno for inspiration and sample generation
“There are lots of professionals that we know about using our stuff, whether it's for inspiration or sample generation and stuff like that.”
Shulman: AI evaluation benchmarks are far worse in audio than text
“As flawed as these benchmarks are in text, they're way worse in audio.”
Suno Uses Modal for Its AI Music Production Infrastructure
“Yeah, so, I mean, they're using model for, like, production infrastructure, like, they have their own, like, custom model, like, custom code and custom weights, you know, for AI-generated music, Suno.ai.”
Shulman: Suno borrowed significant code from Andrej Karpathy's nanoGPT for Bark
“There's a big shout out to Andre Karpathy's nano GPT. You know, there's a lot of code borrowed from there.”
Shulman: Suno is particularly bad at capturing realistic vocals
“One of the places that we are particularly bad is vocals and at capturing really realistic vocals.”
Shulman: Suno focuses primarily on audio tokenization to leverage text transformers
“What we do is we benefit from all of the beautiful things people do with transformers and text, and we focus very hard basically on how do I tokenize audio in the right way.”
Shulman: Over half of Suno usage is in expert mode
“Yeah, actually more than half of the usage is that expert mode.”