 From Milpitas, California, at the edge of Silicon Valley, it's theCUBE, covering autonomous vehicles, brought to you by Western Digital. Hey, welcome back everybody. Jeff Frick here with theCUBE. We're in Milpitas, California at the Autotech Council Autonomous Vehicle Event. Autotech Council is an interesting organization, really trying to bring a lot of new Silicon Valley technology companies and get them involved with what's going on. In industries, they've done Teleco Council. This is the auto one. We're here last year, it was all about mapping. This is really kind of looking at the state of autonomous vehicles. And we're excited to be here. It's a small, intimate event, about 300 people, a couple of cool demo cars outside. And our first guest is here. He's Sanil Mishra. He is the strategic marketing for Tencer. Nice to be here. Thanks, Jeff. I appreciate you having us. Yeah, so give us the overview on Tencer. Sure, so we're at Silicon Valley startup, venture-backed. We're actually just coming out of stealth. So you're one of the first folks to hear about what we're up to. And we're basically doing software platforms to actually accelerate autonomous vehicles into production, doing all the things around safety and efficiency and ROI that will be important when we actually want to make money on all of this stuff. Right, so what does that mean? Because obviously you're in Palo Alto, and in Palo Alto we see the Waymo cars driving around all the time. And it seems like every day I see a few more cars running around with LiDAR stacks on top. Those are all kind of R&D, log-in miles, doing a lot of tests. What are some of the real challenges to get it from where it is today to actual production? And how are you guys helping that process? So yeah, I mean, a lot of what people don't think about is these R&D kind of pilot cars, they actually are doing R&D, right? It's trial and error, right? That's the whole point of R&D. When you get to production, you can't have that error part anymore. And so safety suddenly becomes a critical element. And part of the things of getting safety is being much more efficient on the vehicle because you have to do a lot more software in order to be safe across multiple different kinds of examples of streets and locations and weather conditions and so on. So we basically provide essentially all the glue, all the grunt work at the lower levels to make things as efficient as possible, as safe as possible, as secure as possible. And also at making things adaptable and flexible, there's lots of different hardware coming down the pipeline from all the different vendors. And if you're a production vehicle, it's which ones you choose. There may be different configurations for different cost points of vehicles. And then of course, when you're looking to the future as a production vehicle manufacturer, how do you know which pieces of hardware to use and whether your software will work or not? We kind of give you a lot of insight into all of those things that allow you to certify that your products are safe. And so we just, we don't build the stacks themselves, but we actually take people's self-driving models and we accelerate them onto the vehicles. With your software in the ecosystem of the self-driving car? Exactly, so we have an actual runtime engine that will set on the end device, in this case, a vehicle and it will actually optimize the scheduling and the orchestration of all of your code. That makes it much more efficient and we can monitor that so you can mitigate for safety. And if something does go wrong, we're essentially like a black box where you can actually see what actually happened to your software. So it's interesting, we talked a little bit before we turn the cameras on that a lot of the self-driving vehicles are forwards. We talked to the guys at Phantom and apparently it's a really nice system to be able to get computer control into the control mechanisms of the car. But you said there's a whole layer of how do you define being able to interact with the control systems of the car versus is it safe, is it ready for production and kind of taking it beyond that R&D level? So what are some of the real challenges that people need to be aware of when we're gonna make that big leap? Yeah, so I mean, I think a couple of the big things that happen is when you're seeing these pilot vehicles driving around, the amount of software that they actually have on there to control the vehicles is very tuned for the particular cases. That's why you see a lot of these vehicles out in places like Arizona, right? Sunny weather, you know, having to deal with snow and all the rest of that stuff. If they actually take a car and move it to Michigan for the snow test, they'll actually deploy different software to do the snow case. But when you're actually in a production vehicle and nobody can actually come back and change that software, you're gonna have to load all of those types of solution on at the same time. That requires more space, more compute power. And so for solutions like ours, we actually allow the production manufacturers to figure out what the optimal solutions are in those cases because you can't come back and change the software. You don't have an engineer that can go tweak that code and you don't have a safety driver. Of course, they go grab the wheel if something goes wrong. These things essentially have to be able to go out there in the wilderness for years and years and actually work. So it's a whole different classification of problem. That takes a lot more compute power. And people who are seeing those giant sets of sensor rigs don't probably realize there's also a giant trunk worth of compute power in the back, running 3,000 watts of power. When you actually get to deployment, you're gonna have an embedded system with maybe 500 watts of power. So you have less compute power and you're trying to do more with it. So it's quite a challenging problem to actually jump to production and we're kind of smoothing out a lot of those wrinkles. Right. So I just want to get your kind of perspective on kind of the Apple approach which everyone kind of sees Tesla as. It's soup to nuts, it's the car, it's design, it's the software versus kind of an industry approach where you have all these different players, obviously 300 people here at this event. There's autonomous vehicle events going on all over the place where you've got all these component manufacturers and component parts coming together to create the industry autonomous vehicles versus just the Tesla. So what's kind of the vibe in the industry? It feels like early days, everybody's cooperating. How is this thing kind of coalescing? Yeah, I think what we're seeing is we basically talk to people up and down the stack because anyone who's doing this stuff is a potential customer for us. So Automotive OEMs, the Tier 1 suppliers, so the AI startups are building these software stacks. They're all potential customers for us. What we're seeing from everyone is they're saying there's so many difficult problems to solve along this path that no company can really do it themselves. And of course you're seeing big companies investing billions of dollars but it's great because everybody's saying let's find people that specialize whether it's in sensors or compute or all the rest of those things and build them and kind of get them in, partner with them, have everybody solve the right problem that they're specialized and focused on. And we essentially can kind of come in and we solve parts of those problems but we're also kind of the glue that builds a lot of those things together. So we actually see ourselves as being quite advantageous in that anyone who's doing their specialized piece contributes into the collective and we kind of build that collective and make it easy for the actual end vendor that's trying to sell a car or run a service to actually access all those mechanisms. And are the kind of the old school primary manufacturers still the focal point of the coalescing around this organization or are they losing kind of that position? I wouldn't say they're losing it. It's kind of an interesting place. So you've got a bunch of traditional automotive guys who actually don't really, not to diss them but they don't really understand large scale software because they haven't had that in their vehicles until now. And at the same time you've got kind of your startup mode software experts but don't really understand a lot about automotive but eventually it's got to go in a car and so what we're finding is the automotive manufacturers are really saying to get to production we need certain kinds of safety guarantees and ROI and so on. So they're really driving from that point of view. The software guys are kind of saying well we're just gonna throw the software over to you and sort of good luck. So we're actually finding both sides care but nobody's quite sure who should be taking the lead. So I think we're getting to the point where ultimately the automotive manufacturers will be the ones shipping vehicles and that software is gonna be on their car. So they're gonna be the ones that care about it most. So we're actually seeing them being quite proactive about how do we solve these problems? How do we get from the R&D stage to the actual production stage? So that's where we're seeing a lot of the interest on our side. All right, Sunil, we could go on forever but we have to leave it there and congratulations on your launch and coming out of stealth and we're excited to watch the story unfold. Great, thanks Jeff, I appreciate it. All right, it's Sunil, I'm Jeff Frick. You're watching theCUBE from the Autotech Council Autonomous Vehicle Event in Millpeas, California. Thanks for watching.