No Priors: Artificial Intelligence | Technology | Startups
00:22:17 · Sarah Guo, Mati Staniszewski
[00:22:17] S0: No, I think the baseline is here, so actually I'm by that And [00:22:21] S1: the crazy thing is, I think they are so ahead in actually doing that. And I think there are two concrete things there. One, they kind of combine all those use cases, so we are looking into how they can have effectively customer support of government, whether it's asking about benefits or employment, about the process of how you leave the country. All of that be run through effectively a digital app, then two, how you can have a proactive way of informing citizens of things that might be happening, but then having an education system that also runs through this personal tutoring experience. And all of that is happening. That was incredible to see, and the second amazing thing was that the way they've done it, so they have the digital transformation piece, but they have engineering leaders in each of the ministries that lead those efforts, and then bring them back to that one central piece, so that is like incredible to see, also proud to be able to be working with them on that shift, but despite everything that's happening, they're like so That's amazing.
00:23:19 · Sarah Guo
[00:23:19] S0: That's really encouraging. Can I ask you a business model question here? Because Of looking at the strategic landscape... Actually, have many questions here. One of the observations I'd have is if I look at one of these, like, rich voice and action agent experiences, there's a lot of, let's say, Fortune 500, Global 2,000 leaders who listen to the pod. I think a lot of them are gonna buy the idea of, like, I want this amazing automatic, like, real time available twenty four seven every language experience for my customer that's consistent and high quality. The ways I might get there include working with a Palantir or a large consulting firm, working with Eleven or a platform technology company or an OpenAI or something, right? Let's talk about that. Or working with a more use case oriented company like Sierra. How do you think about how people are making that decision or how they should make that decision?
00:24:25 · Mati Staniszewski, Sarah Guo
[00:24:25] S1: So, my past is also in Palantir, so I started exactly kind of from that side, and we do blend a lot of the forward deployed engineering inside of the company too. As I think about kind of our offering and the customers making that choice, if you're looking just as a one pointed solution and only that one, then likely we aren't the best choice. If you are looking to deploy that across a plethora of different experiences, so be it customer support, but then you also want internal training, then you might want to elevate your sales part and actually increase the top line with new experiences of how you engage customers beyond that kind of reactive piece, then it's a great platform to build, and then we effectively, as we engage with customers, combine that platform work with our engineering resources to help those companies deploy on that, or which we also see increasingly in Fortune 500s, G2000s, where they will want to build parts of the things themselves because they already have a lot of the investments in that platform, while then engage us on some of the new ones and combine those. And I think that our model and the way it's different to a lot of the use case specific ones is that our platform is relatively open, where you can use pieces of that platform and not all of them for those different use cases. Palantir of course will, or some of the consulting companies will have a lot more resources to go in the wider digital transformation journey. In our case, it's, like, very specific conversational agents. [00:25:51] S0: Mhmm.
00:25:51 · Sarah Guo, Mati Staniszewski
[00:25:51] S0: Mhmm. [00:25:52] S1: Like, if you are looking for new interface with customers, that's the the best way. And and companies like Sierra, phenomenal, of course, on on how they are thinking about the the specific pointed use case. And maybe the other piece is, like, as we think about our work, depending on what you are optimizing for, so we have a lot of international partners. If you have a wider geographic user base, great. That's what we optimize for. Our voices, our languages, our support for integrations internationally are just so much broader. There's frequently a piece that you will look into. Depending on your exact scope, this be a big factor, but I would summarize that if you are looking for a solution across a set of different use cases that you want our engineering help and deploy that, then we are the right solution and probably the best solution.
00:25:52 · Mati Staniszewski, Sarah Guo
[00:25:52] S1: Like, if you are looking for new interface with customers, that's the the best way. And and companies like Sierra, phenomenal, of course, on on how they are thinking about the the specific pointed use case. And maybe the other piece is, like, as we think about our work, depending on what you are optimizing for, so we have a lot of international partners. If you have a wider geographic user base, great. That's what we optimize for. Our voices, our languages, our support for integrations internationally are just so much broader. There's frequently a piece that you will look into. Depending on your exact scope, this be a big factor, but I would summarize that if you are looking for a solution across a set of different use cases that you want our engineering help and deploy that, then we are the right solution and probably the best solution. [00:26:43] S0: I wanna talk a little bit about maybe OpenAI and the foundation, LLM foundation model companies. One of the reasons Elad and I called this podcast No Priors is because we're like, okay, people are making a lot of assumptions all the time about how the market is gonna work, and lo and behold, like many of those assumptions end up being nonsense, actually. And you you you can't... You have to very much decide your own narrative at this point in time. I think, correct me if I'm wrong, like in 2022 and '23, you probably heard a lot of people say like, Google can do this, and OpenAI can do this, and like, why do you get to persist working on voice anyway as a general capability? What's the answer?
00:26:43 · Sarah Guo, Mati Staniszewski
[00:26:43] S0: I wanna talk a little bit about maybe OpenAI and the foundation, LLM foundation model companies. One of the reasons Elad and I called this podcast No Priors is because we're like, okay, people are making a lot of assumptions all the time about how the market is gonna work, and lo and behold, like many of those assumptions end up being nonsense, actually. And you you you can't... You have to very much decide your own narrative at this point in time. I think, correct me if I'm wrong, like in 2022 and '23, you probably heard a lot of people say like, Google can do this, and OpenAI can do this, and like, why do you get to persist working on voice anyway as a general capability? What's the answer? [00:27:21] S1: That also adds kind of another element to that, a couple of the other previous questions where whether it's agents work, whether it's the creative work. To deploy the value in those work, you need a very strong product layer. You need integrations. You need to help people deploy the work, which is the most common piece. But our superpower and our focus for a long time was building the foundational models to actually make that experience seamless. And as I think about a lot of the companies in the market, they will optimize for a lot of other things, and that will be the differentiator. In our case, where we will make the whole experience, especially with voice, seamless, human, controllable in a much better way. [00:28:04] S0: And so fundamentally you would argue that the labs just aren't gonna focus on this, and haven't.