Cartesia

“Right now, the only other player who's focused on real time is Cartesia.”

“But they are heavily dependent on state space models and we don't train state space models.”

“We think that AI that's always on, always running, that's able to communicate synchronously with you, is going to be one of the future interfaces for how you consume intelligence.”

“So as an example, we've built our own inference engine. It's pretty important because we think that these interactive real-time models are going to need to run in a pretty different way. So having the ability to have your own engine that is not designed for LL…”

“For us, the mission was always about building interactive AI and closing the gap between AI and humans in terms of how smart and how interactive these models are. So we are always super focused on real time interaction. And that means also, for example, we nev…”

“Again, it was clear that the future is going to be single, single models that are multimodal can process multiple streams of data. Can basically do reasoning over that and operate at pretty low latencies.”

“Today when you build a voice agent, it is actually not running a 30 minute conversation, truly. It is actually running a series of 10:02 conversations, because it is basically splitting the 30 minutes into small turns, And then every turn is treated as one thi…”

“We're seeing customers that are starting to go towards pretty insane volumes now on our, on top of us, like anywhere To like order one billion minutes, right? Getting to that scale a year for one customer.”

“A lot of what we see when people are building these systems is that they're struggling to understand how to bring latency down while keeping the overall intelligence of the system as high as possible. That is the biggest challenge a lot of these folks face.”

“I think there's two variables that matter for those companies. One is how many minutes of interaction are you driving? The other is what is the value of every minute? Because in different applications, every minute has different value.”

“And we believe that to build them, you need to build them on new architectures.”

“We incubated in Chris's lab, right, and Chris is one of our co-founders as well as, like you know, obviously we're his four, like, grad students, so, so we spun out of the lab.”

“So ultimately our ambition is, again, how do we bring together listening, thinking, and response into a single model and just do that continuously. And that's the next phase.”

“I had done one project in speech in my PhD, and that was for three months. So we didn't, we weren't experts in speech, but we knew a lot about sequence modeling. We'd spent a lot of time in, in the deep learning side.”

“I actually think that's the kind of thing that's super exciting, which is that it opens up the opportunity to provide an experience that was otherwise infeasible.”

“Eventually I think what we realized is we made enough progress where it didn't feel as valuable to do the N plus one-eth academic paper. And it actually felt a lot more important to try to figure out how to use the technology work that we've done, and obviousl…”

“Imagine a workplace of the future where actually the way you work is you constantly have this collaborator and you actually redesign the workplace to Help people be able to work alongside the AI collaborator. So you can't have open office spaces anymore, becau…”

“How do metrics shift because you changed how a voice sounds? It has enormous impact in use cases and different use cases need different experiences, right? If you're doing a nursing use case versus you're doing a banking use case versus you're actually doing a…”

“This is something that a lot of people think is mutually exclusive, right? People think either you can be a research lab or you're a product company. Yeah. We, I think what we did was we said, no, no, no, that's not, we don't think those two things are not pos…”

“The only way you can build models like that is you have to go basically co-design everything. Otherwise you're going to sacrifice something for something else.”