What's so interesting about Wayve is no focus on the hardware, no focus on the cores, just the foundation model, the robotic brain that helps a car learn how to drive itself. Let's stop by asking why you felt you needed to bring your testing to California, to the streets of San Francisco. Hey. Well, we're excited to bring a fresh approach to the US market. I think in general, being able to operate an air and powder test in such a diverse market as the US is going to be awesome for us. We really want to push the boundaries of generalization. The neat thing about this approach is that it can allow all ranges of automation, from driver assistance up to full autonomy, with different types of vehicles in different driving environments with different coaches. And, you know, look, we're now training from data from over 15 countries. But to be able to actually have a testing fleet on the ground and show

that I can generalize and drive in a new environment like the US and California. This is a really exciting moment for our business. Alexa, out the pathway from here. You're going to start with basically level two plus kind of ADAS functionality. So you don't need a DMV permit, but what are the next stages? How will you expand the testing and what's your ultimate goal for the California market? You know, fundamentally, Wayve is building an embodied AI. This is an AI that, you know, brings it out of the Internet and into the physical world to be able to drive and operate vehicles. And this is an AI that can understand the physical world, can drive with different types of sensors. And what's really exciting for us is that while we want to deploy it in a range of automotive products, the latest vehicles that have been produced by the industry have used surround cameras and radar.

sensors. And I actually are the perfect deployment environment to reap the benefits of this. Right. So the first model we want to bring is a software model where we can see this air deployed in vehicles, deployed as driver assistance and use that experience and exposure to improve the quality of the system over time and ultimately bring us to this autonomous future we all dream of. You've raised more than ,000,000,000 from the likes of SoftBank and Nvidia, Uber recently topped up the round. How quickly burning through that and where's the money going? Yeah. Look, we've been a fairly disciplined company for the last seven years. Seven years ago, we. We had the thesis of going all in on an end-to-end approach for autonomous driving. And it's something that we've been building out and pioneering some really interesting approaches that allow us to be more data efficient and to learn from simulation and generative AI.

And so while we're seeing a lot of expansion and growth in the amount of data we're training on, we want to continue to make a lean and cost-effective solution possible to come to market. And of course, the partners that we've got in the US that also make us really interesting for us to be able to operate in that in the same market, closer to our partners like Uber and Nvidia and Microsoft that have been really key parts of this journey to power compute and the fleet learning of these systems is going to be so critical.

Wayve Begins US Test Rollout

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