00:13:15 · David Senra, Mati Staniszewski
[00:13:15] S0: to say more about though, because this is where I still am a little confused by this. Somebody doesn't know who you are, they just met you for the first time, they don't know what ElevenLabs is, like, describe to that person how you view your own company. It's like a research lab. Is that the word you're going to use? How would you describe this? I would introduce [00:13:32] S1: consistently the company as a combination of research and product deployment. Research is frontier audio models, text to speech, speech to text orchestration. Product is one platform that helps companies transform how they communicate with the world around them. And that can be marketing with helping them tell a story like Ramp creating their Super Bowl ad. It can be support working with Deutsche Telekom and creating voice agents for the call center, or it can be sales helping on inbound sales qualification to make sure that that streams through. Or even wider operations and working with the government of Poland to help create an agent that can take a healthcare appointment, follow-up with a patient to remind a mother at the appointment, ask how they are feeding. And that kind of one combination between those is building the research, building the frontier of all voice, of all audio, and on the product, doing the part of applying that audio, combining that with knowledge, combining that with the creative work to then allow companies, people to change how they communicate. [00:14:35] S0: And you are solely focused on audio?
00:14:35 · David Senra, Mati Staniszewski
[00:14:35] S0: And you are solely focused on audio? [00:14:37] S1: On the research side, solely focused on audio product. We combine the best of audio with integrations, knowledge, LLMs to help deliver for... [00:14:46] S0: Explain why you think it's so important to be solely focused on audio on the research side. [00:14:51] S1: We think we have incredible talent to be able to go after that. The focus is so important in effectively building the best architecture for those audio models. We think audio is a good combination of not only science but also the arts that you need to solve. It is a little bit subjective. The voices that you produce will be subjective. So you really need to get it right. But ultimately, as you think about AI models, there is data, compute architecture that you need. On audio, we think a lot of the problems that still exist are on the architecture side. We want to be solely focused on solving those architecture problems so you can actually get the best quality out there. A lot of the team, lot of the people that work on our side are the best audio researchers in the world. They're also excited by the premise of being able to continue deploying the best frontier audio models. [00:15:42] S0: And you feel you have technology on the other side that no one else in the world has? [00:15:46] S1: We think so. Yes.
00:15:46 · Mati Staniszewski, David Senra
[00:15:46] S1: We think so. Yes. [00:15:47] S0: It's a weird analogy. I'm so glad I'm reading this book at the same time we're talking because, like, for Honda, they kept kept trying to get him to diversify. He's got other products. Obviously, he builds a bunch of things with engines. But he's like, does that product have an engine? And they're like, no. He's like, then I'm not building that product. He's like, I just do... I focus on engines. And sometimes it's on two wheels and four wheels and everything else, but it's like just engines. It's very similar to what you're saying about audio. And he also said that he felt he had the best engine technology in the world and no one else, could replicate what they did. [00:16:15] S1: There is a common question as we think internally of like, it's 100% true of how you describe it now too. We think about new products, the big question is, do we think we have a unique advantage by applying our audio models in that product experience? If the product experience doesn't have a big bottleneck in that audio and the voice communication side, then it's not our fault. [00:16:39] S0: Explain a situation where you realized that you shouldn't go after that opportunity. Could you give me an example of what you're describing?
00:16:39 · David Senra, Mati Staniszewski
[00:16:39] S0: Explain a situation where you realized that you shouldn't go after that opportunity. Could you give me an example of what you're describing? [00:16:45] S1: The example would... That I'll give you to slightly different spaces. One is on... For for a long time, and I think it's still true, the ideal version in the audio space is if you create a marketing campaign, it's how that combines with a lot of the image and video work to deliver better content. Two years ago, we would have first tried to see whether we can help people create effectively lip dubbing or avatars for for their content. So let's say you switch from one image to another, you need to move the lips, or let's say you want to narrate something, you create an avatar. That was roughly two years ago. A lot of the models that existed on that site just weren't good enough. And deploying a product in this space would be such a defocus and such a shift for the company that it didn't have the audio as a superpower. It still had a bottleneck of the quality of Avatar's quality of a lot of their Because the [00:17:42] S0: problem to solve there is video, not audio.
00:17:42 · David Senra, Mati Staniszewski
[00:17:42] S0: problem to solve there is video, not audio. [00:17:44] S1: Exactly. So this was still poor. So even if you had the best audio applied into that work, still the experience wouldn't be very good. So we decided to not effectively pause any of that effort. Fast forward today is of course shifting now. I think there is a good set of open source models now that exist in that space where the combination of audio, image, and video can actually deliver that result. We are revisiting that today and the recent London ads engine of bringing an ad and bringing that internationally and shifting things in the video, perfect use case of that. But still, a conscious decision we are taking is not creating the model from scratch. So like true text to video or like, you know, VR free type models that exist. We want to be at that intersection where we know the audio can give you the unique advantage, which is usually you already have an existing asset, you need to modify that asset, add that audio component and bring it bring it home. [00:18:36] S0: Do you feel this, like, intense focus or relentless focus on audio is kind of like defense against, the larger labs? For sure. You talk about this in the company?
00:18:36 · David Senra, Mati Staniszewski
[00:18:36] S0: Do you feel this, like, intense focus or relentless focus on audio is kind of like defense against, the larger labs? For sure. You talk about this in the company? [00:18:47] S1: We do. The big part is our focus is audio on the research side and that's where we want to win. I think that we also talk about this in the long, long term, that advantage that we have today will hopefully still be there, but it might not be as big on just the pure research. That's why the other components, that's why the product is so important. That's why the ecosystem is so important that we build around that product. Maybe just to explain what I mean by the ecosystem, of course, there's the brand and trust that you built, but there are also other parts that you can build. In our case, this was investing into effectively a marketplace model where people can create an asset, we authenticate it, and then you can share it and earn compensation as a result. Like trying to create a completely different model for how that works. Give me details about that [00:19:33] S0: because I don't know. Don't know. Yeah.