The a16z Show
00:00:00 · Mati Staniszewski, Erik Torenberg, Jennifer Li
[00:00:00] S0: We don't want to become same as previous generation of of the editing suite. So instead, let's solve it on the research level where it will know based on the voice exactly how it should speak with the speed. To be able to cater to all those different use cases, you need such a big array of different voices, different languages, different accents, different styles. So we launched Voice Marketplace where you you could create your voice and then share it, and when that voice is you earn money in the return. Today, we have almost 10,000 voices. We paid $10,000,000 back to the people the community. There's some crazy stories from the voices. Just speaking through exactly the technology, showing the examples, and kind of avoiding this initial knee jerk reaction that AI is bad has has been has been driven. [00:00:42] S1: Voice is rapidly becoming the next interface for human computer interaction. Today, you'll hear from Mati Staniszewski, cofounder and CEO of ElevenLabs on building at lightning speed from text to speech and fully licensed AI music to real time voice agents, as well as how small autonomous teams and global hiring power the company's product velocity. We discussed the ethics of AI audio, the Voice Marketplace paying creators over 10,000,000, and the shift from creator brand to enterprise platform, plus why speed is the moat in the race to define the future of sound. Let's get into it. [00:01:18] S2: I'm excited to welcome our first speaker, Mati, cofounder and CEO of ElevenLabs. Alright. So good to have you here, Mati.
00:01:18 · Jennifer Li, Mati Staniszewski
[00:01:18] S2: I'm excited to welcome our first speaker, Mati, cofounder and CEO of ElevenLabs. Alright. So good to have you here, Mati. [00:01:35] S0: Thanks so much for having me here. Great to see everyone, and good morning. [00:01:39] S2: Was the walk on music generated by ElevenLabs, was it? [00:01:42] S0: It was. We expand continuously across the audio space. So we started with voices, then created orchestration of how to build voice agents, and now also create a fully licensed music model so can produce amazing music to go alongside of it. [00:01:56] S2: Awesome. We'll talk all about that. I've had the opportunity and also the luck to get to know from the very early days when ElevenLabs got started and got to partner over the last three years to just see your execution everywhere from product launches to shipping new lines and models like you just mentioned, everything from text to speech models, speech to text, and then we started doing music, sound effects, and now the AI agent platform. I'm very curious. First, I'm still in awe of the shipping speed after all these three years, but I want to ask, how do you actually maintain both the speed and quality when you have such expensive product roadmap?
00:02:37 · Mati Staniszewski
[00:02:37] S0: So first of all, we partnered almost three years ago, and so it's great to hear all the kind notes. But also, they didn't realize when we partnered, the infrastructure team was three people. And of course, now I'm ElevenLabs founder. We love number 11 in the company. Infra team is 11 people. So we've seen the growth of the other side as well, I hear the companies here raised $66,000,000,000 in the total fundraising, so the number 11 is everywhere here. But I think that, to start off, I think first piece, I think the smartest person I got to know as my co founder, Piotr, who has been the research brain for creating a lot of the models and then being able to assemble what we think are the most incredible researchers in the voice space to really create the first text to speech model that could understand the context in a better way and turn that into the emotion intonation, then find a way to capture the characteristics of the voice so you have the voice sound with the right style, the right age, with the right gender, dialect, everything in one, And then the researchers across, of course, now expanded that to speech to text music and other work. So that's our foundation. And then the way we structure it to be able to ship quickly, especially with so many things happening in AI space, is a lot of small teams. So today we have roughly 20 product teams, each of five to 10 people size, which with full independence can go ahead and ship products. Of course, that carries some of the sometimes issues of duplicative work or sometimes people going at different speeds, but at the positive end, the ownership of each of the teams is extremely high, so people know that this is down to them to really deliver and ship, and it allows us to move extremely quickly. We bucket our work into creative space, so creative platform where we help with narrations, voiceovers, dubs for creatives and creatives in the immediate entertainment space, and then on the agents side where we help people recreate voice agent experience, conversational agent experience across customer experience all the way through to immersive media.
00:04:31 · Jennifer Li
[00:04:31] S2: Great. ElevenLabs has labs in the name, very similar to many of the other big labs, which means you're doing your first party R and D and model development, but also building all these 20 products. How do you think about balancing both, like keep progressing on the model research, but at the same time not delaying sort of the product launches?
00:04:50 · Mati Staniszewski
[00:04:50] S0: Yeah, it's very tricky. I'm sure many of you have the same thing. Like, do you build a product when you don't know if the research innovation will displace the product you just built? We had this in the early days too, so one of the simple examples was we had a model at work and one of the most common requests was could we do at different speeds for voices, so could you have additional slider to modify the speed of how audio gets generated and how quickly it speaks, And we are very against this idea of, no, we don't want to do any sliders, any toggles, we don't want to become same as previous generation of the editing suites. So instead, let's solve it on the research level where it will know based on the voice exactly how it should speak with the speed. And we resisted this for, I think, a good amount of nine months, and we couldn't solve it on the research side. And then the product was super simple solve that got all the users across. And now the approach we take in looking at this is if we think the research work will take more than three months, then the product is can do anything they want to start adding other models, adding some of the extensions. Of course, sometimes the timeline is tricky to predict, but roughly, the guidance we have from our internal research team, what are the initiatives we hope to ship this quarter, what are long term initiatives, And then for anything long term, you can use any other work to close that gap and make it better.
00:06:04 · Jennifer Li, Mati Staniszewski
[00:06:04] S2: I guess, first, you kind of have to figure out if the research commitment is going to meet the timeline first and then go on to align with the product teams. That makes a lot of sense. As everyone is moving to San Francisco and building in person and locked in in the same space, Eleven has always been building globally and having people more distributed. But you now have centers, I guess, in different locations from London, Warsaw, San Francisco to New York and other places. How do you think about building this global expansion and finding talent globally versus, I guess, the trade offs of building in the same place? [00:06:44] S0: Yeah, so me and my co founder are Polish. We started between Warsaw and London at the time, and I think ElevenLabs wouldn't have existed if we weren't starting from Europe. It's a very peculiar thing, but in Poland, if you watch a movie in Polish language, like a foreign movie in Polish language, all the voices, whether that's a male voice or a female voice, get narrated with one single character. No emotions, no intonation. As you can imagine, it's pretty terrible, and it's still happening today for most of the content out there. [00:07:10] S2: I've had a similar experience growing up in China, that we have a lot of western movies dubbed in Chinese So