WTF Online
00:11:36 · Mati Staniszewski, Nikhil Kamath
[00:11:36] S0: What did he say? He didn't say. Okay. Yeah. My guess my guess would be I don't know. Or if you were... Maybe maybe maybe if you were guessing Right. From what you know, what's what's your guess? [00:11:49] S1: On Sam and Jony Ive? Yes. I feel like for revenue and to really scale because human behaviour is so accustomed to using a device in your hand, I think that's where scale lies initially. So I wouldn't be surprised if it's a phone looking device with a UI which is not natively Android or anything that already exists but something which is a lot more different with a partner with a buddy device maybe which is like a pendant or something like that. Because they don't have a hardware player. I feel like for AI at some point it'll become relevant that hardware comes pre installed with the software which is AI first and to be in hardware for all of these AI companies will become increasingly relevant. Hence, actually, they're nothing bet because I always thought AI company will come in and buy them out at some point. [00:12:51] S0: They can still... I... It's it's still possible. Yeah. It's... It feels... But but in general, like, I think OpenAI has a has a good path to building, like, a personal assistant that's next to you. [00:13:03] S1: Mhmm.
00:13:03 · Nikhil Kamath, Mati Staniszewski
[00:13:03] S1: Mhmm. [00:13:03] S0: So it will need to be some device that you carry, of course, every every every day. Yeah. I I do think voice will be a big part for that strategy as well. Mhmm. I I I... From what I see and hear, they will be ramping out the voice efforts. So Mhmm. That'll be good good competition for us to see whether our quality keeps keeps ahead as with us today, so that'll be a good good test. [00:13:23] S1: It must worry you. Right? Like, I always wonder about OpenAI. All these people use the backbone of OpenAI and they build something. And then given enough time, OpenAI sees it and then they want to build the same thing themselves. They seem to have done that in a couple of places. When I talk to friends of mine in the agentic layer of AI or people who have built great applications on top of a model, they all seem to be scared of what happens to these large language models when they come after the end product. Are you worried about that?
00:14:00 · Mati Staniszewski, Nikhil Kamath
[00:14:00] S0: You know like in a... In our case we are of course continuously looking what it... Like, OpenAI, Google, incredible teams. And probably, like, as we think about the space, the the the biggest potentials of of of effectively competing with ElevenLabs. As you think about the company, and I only started it in 2022, like, the approach from the beginning was doing both the research and the product, so doing the foundational model work for audio and then building product around it. And we think both are important and, like, would define the company where we today, of course, don't depend on OpenAI for for for voice, and and we can stay ahead and build models that are both great in English, great internationally, great across India languages, great across European languages, and that's both for generating speech with text to speech, understanding speech with speech to text, and that's important. I think, like, over the next two, three years there's still so much you can do in voice. Like, we spoke about how you make it more fluid and interactive, I think that still can be cracked in a better way. So, of course, worries us whether we continue being ahead, but it's also good motivation. We have... My my co founder is one of the smartest people. He's been able to assemble an incredible research team, and and they keep crushing it. So [00:15:19] S1: Mhmm.
00:15:19 · Nikhil Kamath, Mati Staniszewski
[00:15:19] S1: Mhmm. [00:15:20] S0: I think they will they will they will continue proving that we can be ahead. But then 100%, you know, we cannot just rely on research. We need to have more both defense points, but also how we deliver value effectively to get customers, so it's kind of independent of the research work. And here, from our perspective, we have kind of two main things. One is we have a creative platform offering and then an agents platform offering. Creative platform is helping with narrations, voice overs Mhmm. Localization from individuals, so from creators, podcasters Mhmm. News articles, through to some media entertainment companies like Star. Mhmm. And then on agents, we help automate voice agents and and and customer experience, training, education. So Meesho would be a great example. [00:16:09] S1: Can you can you describe to us what ElevenLabs does overall, like, in a in a simplified manner that anybody could understand? [00:16:18] S0: We built foundational audio AI technology, so we built models to make speech sound incredible and speech be understood, and then we built products on top of that research that help you create voice agents that can elevate your customer experience, can elevate and train people internally or externally. And then we help on the creative side with customers and how they can communicate with with the user base. [00:16:47] S1: So 50% of your business is creator and 50% is enterprise in a way? [00:16:52] S0: That's right. [00:16:53] S1: And say I'm a creator. How do I use ElevenLabs?
00:16:53 · Nikhil Kamath, Mati Staniszewski
[00:16:53] S1: And say I'm a creator. How do I use ElevenLabs? [00:16:58] S0: The... Let's take this podcast as an example. Yeah. The... You know, after after we we we we we've finalized our conversation, something might have not been recorded, you want to add a line Mhmm. You can post process that with ElevenLabs, make sure that we effectively recreate my voice, we smoothen that line out. Mhmm. That's a very simple part. Then let's take a second step. You wanna take this podcast and you want to localize it outside of English, you wanna bring it to Spanish or French or Hindi. Mhmm. And here, you go to our interface, and you can both automatically dab the entire podcast and then go for any corrections that you need. So when we did a podcast with... Between Lex Fridman and prime minister Narendra Modi, that was effectively going through that workflow. [00:17:47] S1: Did you dub that? Yeah. Mhmm. [00:17:49] S0: And that was, like, going through the Human on the Loop, making sure the corrections are there, and that was, like, well, like, an like an very long conversation, incredible test of the of the software, but then you can enjoy that in in a number of other languages. [00:18:01] S1: How much does it cost, say, example, how much did Lex and our prime minister... How much did it cost to dub?
00:18:01 · Nikhil Kamath, Mati Staniszewski
[00:18:01] S1: How much does it cost, say, example, how much did Lex and our prime minister... How much did it cost to dub? [00:18:08] S0: You know, this one was harder. In in general, like, if you just wanted to automatically dub, then, like, an hour podcast will be few dollars, up to few dollars. Mhmm. But with with any conversation like like the one of the prime minister, we did employ a wider set of of people that would actually check every translation, with working with the Lex team and the other side of the team to to make sure that the content is preserved, like, we we know... It's like calibre of the conversation where every word matters. So that was maybe a more unique on that side. [00:18:42] S1: We have this use case. We want to dub all the content we make into regional languages, but we've been struggling with solutions really. More than the cost of it, I feel like the emotion behind what is being said is always lost and everything sounds a bit robotic. How do you change that? I've not tried ElevenLabs.