The Exchanges

Q And because of Daniel's advice, just like, stay away from the circus, like, the people that show up at these things, they don't, they aren't doing any work, they're just there to distract, like, you don't have to do it. And so then I get all these emails and invitations, like, come to this thing, and I open it up, and I see your face everywhere. What are you doing?

A No, I usually try to do two per, two to three per quarter, usually conferences or events. Um, but in our case, it's a little bit different because for a lot of the people that are usually on the conferences, they are partners or prospecting partners or clients. So, so it, it is usually a great way of forcing function of having them in one place and trying to figure out how we build together. That's the benefit of the breadth of the work we do that a lot of, especially on the conversational agents work. That applies to most of the businesses of how they think about communicating with their customers, how they are thinking about changing customer journey. So, so a lot of the, the, the events are, are a great, great way for us to, to, to, to, to catch time with a lot of the, the people that we work with.

AI assessment note: “I usually try to do two per, two to three per quarter”

Q Well, say more about that. What do you, can you not do today in the way you run your organization that you hope AI can change in the future?

A I think there's, um, like always you want the information from the, the, the kind of the, the person working as closely to the problem. So let's say you're developing a product you want to work. You want to speak with the engineer that actually develops that product rather than their manager. If it's a client conversation, similar, you want to understand what is that client saying from the person on the ground, rather the manager is summarizing that information and giving that to you. And I think that that information flow will change with AI where You will have access to everything that's happening in a better granularity than you could ever have before, because it summarizes that back and back and forth. Second, I think that In general, roughly at 11 labs, most people will have close to 10 direct reports. It's a pretty, pretty wide set, which helps us build that small team approach that we, that we have. And that too only works if you, if you can amplify a lot of what's happening across all the teams, all the people that you, that you work with, um, to summarize information of what's happening in their teams, how they're performing, what are some of the gaps, That definitely helps, and helps shift it from reactive to proactive, I think, too. But what I mean by this is, frequently in the past, I think you would rely on, on, on specific individuals surfacing the information to …

AI assessment note: “that information flow will change with AI where You will have access to everything”

Q Explain a situation where you realized That you shouldn't go after that opportunity. Could you give me an example of what you're just, you're describing?

A The, um, example would, I'll go to slightly different spaces. One is, On for, for a long time, the, um, and I think it's still true. The ideal version in the audio space is, um, if you've created a marketing campaign is how that combines with a lot of the image and video work to deliver a better content. Two years ago, we would have first tried to see whether we can help people create effectively lip dubbing or avatars for, um, for, for their content. So let's say you switch from one language 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 the 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 avatars, quality of a lot of them.

AI assessment note: “deploying a product in the space would be such a defocus”

Q That had to be appear like a tiny business though, right? At the time. Like if that's your initial idea, you were, you didn't go, you weren't going into it thinking this is going to be a giant business. Like you're one of the fastest growing startups today.

A You know, we, we actually thought it was a huge business at the time too. So we thought it's like, if we think about all the content, all the stories out there, how incredible if they were available in audio and, and, and, and it's, it's the, whether it's some of the biggest streaming companies, whether that's TV, whether that's the conversations, all of those could be, could be actually delivered in the local language. So we fit it. We thought it's actually huge and we still think it's huge. And then if you shift this to, to even the conversation we are having now, could this be in the future, this version where I speak, Polish, and you understand me in English, or I speak English, and you understand me in any language that you want. And Hitchhiker's Guide to Galaxy, there's this idea of a bubble fish that you put next to the ear, and you can understand everything around you regardless of the language that you speak. So we knew that we will get there, but initially it was like dubbing. So I'll give you like a full, full, full way of how kind of it progressed. Initially it was dubbing, and then as we started diving into what we need to do to solve dubbing, we realized there are three steps in dubbing process. There's Transcription step, then it's translation step to another language, and then you need to regenerate that in another, in another, in another language. Um, but the r…

AI assessment note: “we actually thought it was a huge business at the time too”

Q I'm gonna ask you one more time. I just want to go back to this in case we missed anything. Is there anything else that you learned working at Palantir that we didn't talk about that you think is valuable?

A Well, this is a stretch and I'm biased, biased, but, uh, in Palantir, frequently there was this concept of like how, um, how, You, you, you need, you need a little bit of the understanding of the art to do your job well, or like people need to, uh, um, need to effectively try to be artists, even if, if, if, if, if we aren't, uh, uh, like one of the phrases that was used was artist colony. And if that was ever publicly said, I never fully appreciated the strength of that, but I do feel like a lot, a lot more about this now, as we kind of intersect that AI and creative space in many ways. Whether it's building the audio research models, there's a lot of new ones in how that's delivered. Like, even the, even every voice that is delivered, you like George in 11 Reader, like, everybody will have their own preference, and, and how you make sure you capture those voices, how you deliver those preferences is, is, is a tricky challenge. And then, too, as you work with some of the brands that are trying to define how they communicate with the world, that, too, requires some, a lot of the, of the art in that. And we're trying to, to bring, of course, a lot of the, the people to combine that. Blending that art and science, Pantier definitely tried to do. I think I'll let Lauders judge to do it successfully, but we also will, will try to do and, and, and hopefully are doing good steps in th…

AI assessment note: “in Palantir, frequently there was this concept of like how... understanding of the art”

Q Yeah, they start with one, but you have 10 different products you could sell them. So how do you go from one to two, and then two to five, and so on and so forth?

A Yeah, I think the main thing is, one, And you, of course, deploy the first one. You'll make sure that there is value behind that. So across any customer engagement, we try to make sure that we don't only prove concepts. We prove the impact, prove the value. And only after that, we try to get the companies working with us at the broader scale. So we prove the impact on the marketing side to get the support going. What you actually need to do is not only the audio, you need to build integrations. So you need to connect it with All the CRM systems that, that Deutsche Telekom works with, you need to work on integrations with the output. So how do you connect it to the phone system, or the SIP tracking or Twilio, how you make sure that that connection exists. So you would spend a lot of time on integrations, making sure that their logic is respected on how, when you do pick up the phone call, the agent behaves the way you want it to behave. So here are four deployed engineers, would partner with the team, spend the time, and in Bonn in this case, in Germany, Working through side by side together on the integration, on just being able, making sure that the agent follows the flow that you want, has the knowledge that it should have, and then In that step, the, the, the hardest thing in any voice agent, uh, work is actual deployment of how you actually test that it works. Um, so then y…

AI assessment note: “We prove the impact, prove the value. And only after that, we try to get”