Dana is an agentic platform for physical AI that lowers the barrier to entry so that a high school kid can make an autonomous system, just as iPhone SDKs let anyone make an app—democratizing autonomy development.

48:49is so great? They're just not attractive jobs. >> Yeah. And even trucker even truckers don't want their kids to become truckers like it's it's for that reason why they you know they want their kids to be in a safe at the very least like safe safer safer line of work. >> But um do the do the notwithstanding all that do they how long will there be do

49:04you think there will be safety drivers in long haul trucks that are that are self-driving or or or let's say other even just somebody in the cab to deal with what happens when they arrive? >> We we know multiple companies that have driver goals right now. Okay. So like they're they are working to get drivers out right now. Um >> you know without going into our own

49:20details [laughter] >> to be honest it's not long. We're talking talking a few years and uh >> I think on the long end. >> Yeah. On the long end. And the thing is it's it's a there there's a software technology thing which is one part of the problem. But the other part is it's the redundancies that you need in hardware and the validation necessary for those redundancies. And in many

49:38cases that can actually be a long pull. It's like, oh, they're productionizing a fully redundant steering system, fully redundant braking system, that's that's not in high that's not in high value production yet. And once you get that in high value production, now you got the quality up and then that's validated and now you can actually do these >> near the price downs. Exactly. >> Do do you guys do do you look like it's

49:55the you know these little delivery robots? Like is that do you see a world where there's a billion of those running around? >> Yeah, I think so. I mean the uh the the the product that we're announcing I think it's probably come out around with this time is called Dana. So there's you can just simplify everything that applied intuition does into two buckets which is the we've been talking mostly

50:12about the models that go on the machines then this is we say onboard software or onboard AI then there's offboard AI this is the tools to design and develop these same systems the models that actually go on the machines our uh you know vision for that is and the the delivery robot is a great example is like a high school kid or a middle schooler they can make

50:34iPhone apps they should be able to autonomous systems. So why can't they just ask that's a very simple question. Why can't a >> ninth grader make a delivery robot in their in their home? Well, they don't have the the actual environment that they would first develop the scenarios in. They would define the requirements. Hey, I want this robot to go on my high school campus around these let's say

50:56four buildings. >> Uh then how okay now that you define the the requirements then you have the scenarios get made. where are all the scenarios that can that can uh that can be made by using let's say a satellite image of the high school. Uh then now you have to train the robot. So you need some data. Where do you get that data? There's maybe enough publicly available