The product is essentially an acceleration product. You know when it's working and when it's not. Like you can see around you. You know you get it in Uber, you know if the driver is good or not. It's the same thing with this. We're basically like half car enthusiasts and half people who never want to drive.
What's up everyone? This is car dealership guy. You're listening to the car dealership guy podcast, which is my effort to give you access to the most unbiased and transparent insights into the car market. Let's get into today's episode.
All right, this was a fascinating episode. I think autonomous vehicles in general and the whole idea seems like a very kind of fringe concept to many people. I think John Hayes is an interesting person because he's taken this idea and he's bringing it to reality. I think what they're doing is just a very different approach to autonomous vehicles. He really dives deep into that. He dives into the business model to the economics, how much money they've raised, how they're different in Tesla. Please don't forget to let me know your feedback. Just write tweet at me. I'm really curious to know what you're thinking, so I hope you enjoyed the episode. Let's get into it.
All views of car dealership guy and guests on this podcast are solely their opinions. None of the views expressed should be treated as financial advice. This podcast is for informational purposes only.
John Hayes, welcome to the pod.
Good to be here. I've been really looking forward to this episode. I'm super curious to know about Ghost and just autonomy. We haven't had a CDG podcast episode on this topic, but there's a lot of things moving and shaking right now. I think before we get started on Ghost and what it does, can you just give us your brief background? How did you enter this hardware or software space? What is your background? How did you get to this point?
Light background is building software. I'm coming out from Canada right after college. I moved to Silicon Valley, joined a startup. I went through a virtual world startup, through a talent search startup and worked at Yahoo. Then the first big break was the company called Pure Storage, which was data storage on Flash Memory. We started that in 2009, we went public in 2015, which was about as fast as you could. The economy was really great back then. And then around 2017, I was getting that itch to start something new and I started Ghost. And so each time I'm changing domains, the interesting thing about Ghost is it doesn't really have anything to do with data storage. What it does have to do with is the observation we made back in Pure Storage was that consumer technology was leading into the data center. That's where all the innovation occurs, that's where all the volume is. What do you mean by that? What do you mean leading to the data center?
Okay. So what we saw back in 2009 was you had just the MacBook Air had come out. The most expensive laptop had Flash. It had an SSD in it. You also saw the $200 laptop also had SSDs in it. And so you see the top and the bottom of the consumer market. And so what we predicted was no one would have any hard drives in the consumer market anymore. And what that moves is tons and tons, like billions of dollars of R&D to keep making this product better. And our assumption was that over time that solid-state storage in SSDs would get better faster than hard drives. And that basically came true. And if you look around your life, you don't have any hard drives anymore. And so our assumption was that R&D path would mean that the Flash member would take over absolutely everywhere. And so what we did was we took those consumer products that no one said everyone said, wouldn't work, wouldn't be reliable enough, and built some smart software around it and put it in data center where it runs 24 seven under the most durable applications.
So essentially, you brought storage to the cloud?
Well, storage was in the cloud, but it was on a much cheaper medium, much more reliable, well proven medium.
Got it. And did you take pure storage public as CEO?
No, I was not CEO. So this is the first CEO job for me. I was a technical leader in that company. And so now I'm stepping up to CEO for the first time in this company.
So what was that like? I mean, you mentioned 2017, I saw, I noticed you were working at a VC fund in 2017 for a short stint. Was that the point where you had, you know, ghost, you had this idea, and then you left? Or how did that work out?
So I was there as an entrepreneur in residence. And so what that means is kind of like entrepreneur welfare, where they pay you a salary, they give you a better welfare. And you're supposed to come up with a billion dollar company idea over like sometimes over a year, sometimes over two years. And so I was there for the purpose of starting a new company. And I met my co-founder, Volkmar there. There were other companies started out there at the same time.
And so for those few months, yeah, I was just, you know, going in every day, researching what's new in technology, because there has to be something new, like there has to be a reason to start a company, something that's changed. And then what market could be applied to? And the transportation automotive market is just one of the biggest markets in the world. And so if you can find technology to apply to that, that's going to be a great business if you can execute it.
So explain to me simply what is Ghost? What is the thesis behind the company?
请简单地向我解释一下Ghost是什么?该公司的主要论点是什么?
The thesis is that when I live in Mount of California, so I see all the robo-taxi companies, Waymo's based there. And the thesis is is that when you look at how people actually use transportation, you know, you add in all of taxis, all rideshare, all public transportation, all bicycling, and adds up to 2% of trips. And so what I saw was that no one was going after the 98% of trips, which is people driving their own cars. And the barriers to that were, one, the hardware had to get much, much cheaper. And so when you see a robo-taxi, at the time, it was probably like a couple hundred thousand dollars of hardware. And they think they're going to get that to maybe tens of thousands, but that was never going to be the right scale to put on a consumer product. And so we started with a baseline where we wanted to assume that let's assume you put like a thousand dollars, like of cameras and computers, like really, really pair it down. There's something that you could put on every single car and then build autonomy software to make that work. And so that was the naive thesis back in 2017.
Yeah, and I want to hear how it evolved. But you're basically saying, let me retrofit someone's car so that it can become some form of self-driving, basically.
That's how we started out. So we were thinking, it's like, oh my god, the car companies were very difficult to sell through. It was a very long path. We got to consumer. Yeah, we would go direct to consumer. And starting about 2021, we decided to reorient the company and say, no, no, we're going to sell to auto manufacturers because they started wanting to have that conversation. So when we started in 2017, a typical response would be, oh, the auto companies will build what you're building. Like, because 2017 supercruise had come out, Tesla autopilot was out. It seemed like they could evolve their products. But now starting about 2021 or 2022, you're seeing a lot of turmoil in those projects inside the auto companies. And so now they're changing their tune where now they're actually looking to buy something rather than try and build it internally.
Why is that? Is it just, you know, they can't get their shit together from a tech perspective? Is it just too hard? Well, what is it?
为什么会这样?难道他们只是无法在技术方面做好吗?是不是太难了?那又是什么原因呢?
I think that there's two things. There's a big thing. So one is that auto companies have not made software first-class engineering discipline. And so the hierarchy is built on mechanical engineering, electrical engineering. And when you look at the senior leadership, who came up through engineering, who didn't come up through marketing, it's almost always those two paths. And software engineering is just a completely different discipline. So they're trying to build these organizations, and they have to be run differently.
The other thing is that there's no evolutionary path between something that unreliably flashes a light at you and something that will actually drive a per 100% of the time. There's just orders of magnitude more complexity. And so, I think that they've discovered that they can't evolve from features like individual safety features and maybe some lane centering into something that's full autonomy, and that they're built in a completely different way.
So you think you can get the car that's in my garage right now to actually be full self-driving by just retrofitting some equipment on it?
那么你认为只需给我车库里的那辆车装备一些设备,就能使其实现完全自动驾驶,是这么想的吗?
Well, we think that the next car you buy will have the right equipment to be autonomous. And so we target it. But it won't necessarily be autonomous. That's up to the auto companies. But what we target is the exact same computers that they're already building into cars. So these are, you see it in the entertainment system, the exact same cameras that they're already building into cars. Like it seems like every car now has between like four and nine cameras and the radars and tying that together into an autonomous system. And you especially see this with electric vehicles where they're just changing the entire architecture to make it centered around a computer instead of being centered around the motor.
Can you explain to me the different levels of autonomy? I think before we even talk about, you know, the capabilities of ghosts, I'm trying, I want to level set and understand what exactly you're striving for here. The levels of autonomy are usually thought of as the number levels, like one, two, three, four, five is unattainable. It's some future that may never exist. One is like cruise control that we've had since the 70s. Okay. So most of the products you see on the market are level two, meaning that they do some assistance. They do some lane keeping, even things like blind spot information systems counted level two, like everything is just laughing because my wife hates it. Like the car will suddenly stop her and she'll just freak out because she's like, dude, it's completely surprises her out of nowhere. Yeah. And you probably find when you rent a car and like makes a noise at you and you're kind of confused as to what that noise is. That's a level two feature.
And so, and so then in between you have level three, which is this strange zone where you've seen Mercedes implement a level three where they do a traffic jam assist. So if you're going slow, like under 35 miles an hour in just the right conditions, you can look away from the road and the car will just coast along. And BMW is talking about bringing up the same feature, but they're going to go up to 40 miles an hour. And so often it's just very limited conditions. And so the thing that everyone really wants is level four, meaning that you can set a destination or be driving along and you don't have to look at anything. The car will maybe try and track your attention. But if you don't give it to the car, then it will pull over to the side of the road. Like if it thinks it can't continue, it has enough self diagnostic that you don't have to be watching it to make sure it's not going to do something crazy. And so you've seen this appear in two places. So one is in robotaxis. So coming as like way among crews are the most prominent. You're seeing it in trucking. And more recently, you're seeing level four in China. So China is actually on the leading edge of taking level four technology and putting into consumer cars. And you can go there and like try. And that was a big shock to the auto industry. You starting earlier this year.
What's Tesla? Tesla would themselves, they would say that they're a level two in that you have to watch it to make sure that it doesn't do something crazy. It works much of the time, but not all the time. Clearly, their engineering goal is to get to a level four, where you don't have to watch it. But they had to do probably years of improvement to get to that point. Yeah, but how is it possible it's level two? If you know, there's you see people just, you know, going to Tesla, obviously they say you have to, you know, hold the wheel or whatever for liability. But what is it really like practically speaking? I think practically speaking it's level two. And that's because if you just let it do it at once and you don't pay attention, you will have a clue. Almost everyone who is driven Tesla has found a moment where it scared them. And I think, you know, I live in California, I'm surrounded by Teslas and Tesla drivers. Everyone has sort of learned where it works and they turn it on and off, depending on where it's going to work. And I think that that's consistent with Tesla taking a very breadth-first approach. They wanted to do a little driving in a lot of places.
What we're focused on is doing extremely good driving in fewer places. What are those places? Mainly freeways, like freeways express ways, highly structured environments where you don't have a lot of pedestrians and bicyclists and other road users like that.
You mentioned Waymo, you know, cruise comes to mind. What are the key differences here? I mean, you hear a ton about Waymo and Cruise that you're always in to press, you know, so what are the key differences here between Ghost and what Waymo and Cruise are doing?
So they have two major differences in their technology. One is that they use specialized sensors called LiDARs, which were originally used for engineering and site surveying. So you can measure exact distances with pretty good density around you. And so it's used for making a 3D map of an environment. The downside is they have to be outside the vehicle because it's laser, so it goes along the line of light. And they're quite extensive and difficult to maintain.
The second thing is that they use technology called HD maps, where they program in all of the detailed rules of how to drive on a particular street into a database and they use that database. And so mostly what they're looking for with their sensors is the other road users like cars and, and, you know, pedestrians and all the all the mobile things that they can incorporate into the HD map. And so that's why you see Waymo launching in particular cities because they spend up to a year before that doing a detailed survey of the city to build up this database of how the roads are connected and what all the rules are.
We're taking an approach that's more similar to what Tesla is. So one, we don't use any specialized sensors. So our thesis is that, you know, ordinary cameras, again, there's an amazing amount of our data-approved cameras, plus AI means that you don't need specialized sensors. The second is we drive in what you call first-person mode, where instead of trying to anchor against a map by saying, where am I in the world? What are the rules at this point? We just interpret the scene visually as it comes in. And then the maps we use are ordinary navigation maps. So there isn't detailed information about exactly where you should drive on the road. Instead, we orient to what you can see. And so the advantage is that you make a system that works in a lot more places. So anything that looks like a highway it'll work in. You don't need to have pre-surveyed that. But the main thing is it's much cheaper and much lower maintenance.
Do you have an active prototype right now? Yeah. Yeah. We've been driving up to 5,000 miles a month in California now in Detroit, and we just crossed the border into Canada. It's just this week. So that's exciting for me as a Canadian. I put a tow back in Canada.
Wow. What was that like for you? Like were you the driver passenger? What was that like? I was here in Toronto. So our team was out the border. So they crossed the border. They have some pictures under the Canadian flag. So we're going to be letting people know that's happened. And maybe letting the police know because they didn't quite answer their phone. So we stayed under the radar enough, even though it's a totally wrapped car. So it looks unusual. But yeah, it worked perfectly. Canadian highways are pretty similar to American Highway.
That's incredible. What was that feeling? I'm curious, like the first time you stepped into that car and you started driving, were you scared? You're like, I hope I don't fuck this up. It's almost like Jeff Bezos going on the the Blue Origin Rockets. Like, you know, I hope this thing doesn't explode when I think it. Yeah, it's probably not that dangerous. I mean, the first time we started driving late last year, like August, and the first time you go on the road, it did not work well. Like the steering is wrong, the speed is wrong. And it just takes like months of just sitting there and tuning it and fixing problems over and over. But that was the culmination of four and a half years of development and finally bringing it all together for the first time was just amazing for the entire team. It's like we just had we were just set up on the highway and just having people take runs. It's like, hey, this really works end to end and it's built on and there's nothing magic in the system.
So on that note, you mentioned four and a half years. What are the ways I like to come up with questions for my podcast is I just like to put myself in founders or CEOs or an executive shoes. And I do like this, you know, real timeline.
And one of the things that I thought of when I put myself in your shoes, I said, 2017, we're now in 2023. Like they say, you know, being an entrepreneur is like, you know, eating glass or whatever. I mean, your feedback loop is like, in existence, you know, like you're not yet selling to market or, you know, maybe you're working on deals, but you're not like in market yet.
And you're talking about six years of development building, trying to prove something. How like how, you know, and especially given you said you were from enterprise before that, I mean, enterprise, you build a product, let's go, let's get the first sale. It's like right away. Let's get that. Let's get that dopamine. Hey, let's bring some sales at the door.
So how, what is it like running a company where for, you know, five, six years, it's like, you know, I wouldn't call it maybe an in existence feedback loop, but it's a very, it's tough, you know, and especially a CEO motivating the team. What, what does that like for you?
It's, it's even more interesting with the investors who would, of course, love to see feedback loop because they're putting a lot of money into this year after year. One of our investors, Keith, your boy, you know, his theory is, I just tweeted that. I just tweeted that. Yeah. It's, it's sort of the, the anti lean startup, which is like, no, what you should do is it's like making a movie. You should make the movie and then sell tickets to the movie. Like it's your vision to make that work.
And I think that we're in a space where it's a bit like the last company where the product itself is, is obvious in a sense. In that if you sit in a car and the car drives, it's the right product. And you know that it's product that a lot of people want. Yeah. And that's where this company is very different from previous companies where, you know, I, I'm not going to buy a storage system for myself. You go home for Christmas and what do you do? It's like, I build data center equipment. This is like obvious. And when you sit there and we, you know, when we bring in partners from auto companies and share ones and they send the car, they're like, Oh, yeah, this is working. This is obviously working.
And so, so a lot of it is one, I would say the harder part over that time was there was a lot of false starts. It probably took us, we had a long R and D pair, we had to solve some fundamental problems. Like, okay, you have a camera, you want to measure distance. What are your ways? And we went through about four completely unique ways to do that. You want to figure out the road geometry went through three completely unique ways to do that. We've rewritten how we do planning. Like, how do you decide where to drive? That's been totally rewritten three times. I think it's on the fourth. How do you control the car? That's been rewritten three times. And they think that to keep the team motivated, first, our team is mainly engineers. And so the cost and improvement is in solving problems.
Yeah, solving problems and having the sort of the right sense of when should you start over and build something completely new. And we've done that multiple times over the years to get it right. Because otherwise you get stuck and you make a lot of compromises. But this is definitely the longest development cycle I've ever done in my life. Because we're at six years, we probably have at least another year of pretty hard development. We're starting to get some feedback from the auto companies now. Some of it is determining their psychology. But you have to create internal posts. But a lot of it is making sure that everyone in the company goes in the car at least once a month. And they can see that it's getting better and get that sort of, the product is essentially an acceleration product. You know when it's working and when it's not.
You can see around you, you get it in Uber, you know if the driver is good or not. It's the same thing with this. And that's also been essential for helping people figure out what they should do next. Because they know something is wrong. How can I contribute? If I work out controls, I can make the controls better, I can make the visualization better. And so it's very personal. Almost everyone who works at the company wants this product. We're basically like half car enthusiasts and half people who never want to drive. And so everyone wants it. And they know what they want from themselves. And so as long as they see that continuing to prove, that's where the motivations come from.
What's it like to actually retrofit a car? Is it like, hey, come to my garage 30 minutes, let me slap some hardware on this thing? Or what is that like?
Well, so when we build cars, it probably, it takes like a couple of weeks because the guys like literally take apart the entire car we're doing interfacing with the controls of the car. We have to add computers into the car. We wire up cameras all around. Some stuff is glued on. Some stuff like all the doors come off. And we install radars. It's a process that takes weeks right now. And that's one of the things that convinced us that this really does have to be manufactured in. This is complicated enough that doing after the fact, we'll probably be hundreds of thousands of dollars to do retrofit. And retrofitting isn't a great market. People just don't spend that much on cars after they buy them for things that aren't maintenance.
Yeah. And I think also the other thing to consider with consumers is, if I retrofit my car, did I avoid the warranty? Yeah, no one knows. It's sort of uncharted territory and the auto companies will threaten that you have. Yeah, which is where I think it makes sense to partner with auto manufacturers, almost be like an authorized whatever, so that you can just cross that hurdle.
Tell me more about the economics of this business. I have a couple questions. Starting very high level, how much funding have you raised?
So we've raised just over 200 million funding, about 230 million. And so all of that has been equity funding, mostly entirely from financial investors.
Who was your first investor?
So first investor was Mike Spicer out of Silver Hill. He was also the first investor in pure storage back in the day. So had some confidence that we would make something work.
Had some confidence that you know what you're doing.
Maybe, maybe. Hopefully. Yeah, hopefully. Okay. And so what's the money being put towards? Is it development, employees, anything else?
It's almost all R&D. And what's nice about making an extensive hardware is the cars themselves are at that expensive, the building that expensive. So almost all of it is R&D. And it's probably two-thirds software, one-third hardware R&D.
Got it. And so this is the previous company, Pure Storage, it was like a lot of raised capital went building an enterprise sales force, because that was it. Well, we have 12 customers in the world. So it's almost all R&D. And we're selling into the engineering departments of those companies.
And what's your cost of, you know, a piece of hardware to equip one car? How much does that cost?
So the final cost to build should be under $1,500. And yeah, for the company. And then for the consumer or the manufacturer, how do you think about that? So the way we think about it is a bit different. One, we're not actually interested in making money off of hardware. You know, you put a computer in a car and it's going to be the same computer. And I think that cars would benefit from standardizing that the camera we buy from a camera maker. We don't make cameras. Someone else makes it. And so our goal is to get the car companies to just put a computer in every single car. And then our business model is based on licensing the software at the point of activation. And whether people pay in terms of an upfront cost or with a bit of monthly cost is neutral to us. Because we don't have expense until they actually start using software.
So you're basically betting or you're goal, what you're optimizing for is to make to for the manufacturers to put the necessary equipment as a just natural course of progression in these cars. And then you piggyback off that, that hardware that's already pre installed. And you sell them to software, which is like light years ahead, because you've been working on it for so long and you've come such a long way.
Yeah. And this is a very different business model for the auto manufacturers. We're very used to saying everything I sell has a piece of hardware and the cost associated with it. And then they have to inventory manage all of that. And we're saying no, speculatively, put a computer in there that you'll probably use anyways, because you still have your screens that you have to run, you still have level two features, like it's not going to go completely unused. But you're speculatively putting this in there, knowing that a pretty good percentage of customers will upgrade and use all the hardware.
What are you building specifically on a software side that you think is defensible? Like if I'm, and I agree with you that the manufacturers, they don't have that like software engineering muscle or that's not at least our core competency. But what is it about go specifically that will get you to a point where you know, you are the software they need, they have to come to you as opposed to, you know, a competitor or building it themselves, whatever it may be.
So software is always an accumulating advantage, meaning that hardware, you redesign the whole thing every few years. And you see this with cars where they come out with an all new car where they pre-rese-rese-side everything. But software, you manage over very, very long periods of time. And so you have a cumulating advantage and you have in that you just add to it and add to it. And you replace the hardware underneath and that's okay. And that's how all the software you use has been developed since the beginning of time. So if you think about it, it's like you replace your iPhone every couple years, but all the software remains the same. And it just follows and you substitute that out.
Now, the other thing about the economics of a software company is the more users you have, the more RDR. So you have this positive feedback loop. And I believe that the auto companies themselves, none of them have the scale necessary to do real worldwide development. And it will always be an external vendor that can have enough distribution through multiple car companies in order to feed the R&D to actually develop it. So some of it is, we're very good at running software projects, but there's a reason why in a lot of domains of software, you tend to have winner take all solutions because once you get that flywheel going, whoever has the most users has the biggest R&D budget has the most efficient sales. And that's especially true in AI products where you have the most data flow as well. But then in general, like let's talk about competitors.
So the main competitor, the market leader right now is Mobileye. Mobileye has been oriented around selling a chip. And that's been their whole business. And if you look at their business model is how many chips can I sell? And they haven't yet transitioned to being able to sell software in order to and just letting the chip be a commodity. So we would rather let let Qualcomm, let in media, you know, they have other markets for their chips that's driving their R&D faster. And they're going to make their chip better faster than Mobileye will make it faster. Because they just have much, much larger distribution than hundreds of millions of units. And so what we're betting on is that platform will get better. And then our software, because that's our sole focus will get better as well.
Who do you think are from the car manufacturers? Who do you think is the likely winner here? As this as the scales as, you know, we think, I don't know, five years down the road, whatever, who is the winner here? Which you mean by winner? I think who gets the most who gets the most adoption and who benefits the most from this from the car manufacturers? It's always it's a very fragmented business to begin. Like, there is there any car manufacturer with more than 5% of any market? And I don't I I don't know exactly why that is. But I think what I'm seeing is the American car manufacturers are probably the most ahead. And then the Europeans, the Koreans are, you know, they're behind, but they're aggressively catching up. And you're talking about autonomy. Are you starting to want to must trip economy?
Yeah, autonomy. Just where they are in autonomy. And the Japanese car manufacturers are cut of nowhere. I the stalking horse in everyone's mind is where the Chinese manufacturer is going to do. Since they're going to be entering the market, maybe by the end of this decade, with electric vehicles that are much cheaper than anything that can be produced by a European or American manufacturer. And they're far ahead on software in comparison to those companies. So that's going to be the big rebalancing is like, how much market share are the Chinese companies with their large domestic market and large distribution going to take away from the incumbents?
On a on a bit of a different note, as you as you're talking about all this, you know, the technical details and I'm thinking about building this company again, what was it like for you through COVID, especially being, you know, car focused, like just hardware software? How did you how did you do that? You know, like remote work in person work? And you know, enterprise sales background, tell me a little bit about that.
So we went a lot remote that are hard to team and our operations team never went remote because you're working on a physical car. It's like you can't put a car at everyone's house. We were probably remote until like middle of 2021. And then we started bringing it back. This is probably earlier than a lot of other companies. And remote was pretty difficult. Like it was not nearly as productive because it's not just that you're working on cars and that your product. The thing that saved us is at the time we were doing a ton of driving because we were still developing a lot of foundational technology. But the but having people co located is a huge accelerator for that. And so I think we slowed down a lot in 2020. And I think a lot of companies did. They slowed down a lot. And it wasn't until we really brought back people back in say 2021 that we started accelerating again. And we went from a complex system that just was not stabilized. Like we ground on that for like six months to what's the simplest, most brute force thing you can do to make it work. And so that's just happened over and over and over again. Where you don't know it's like, is this possible or not you're doing something hard? Are we just like not smart enough? Like is anyone able to do this? And you just have to back off and just try something that's a lot more obvious. And then you can get back into a learning cycle where you can figure out how to make it more complicated.
Yeah, I can see that makes sense. You mentioned earlier on the conversation, going back to just autonomy, you mentioned that you're you're targeting, you know, the mass market and like these are freeways expressways. Well, why is that like, is it do you think that you also mentioned that level five is so that this utopian vision? Is it really do you see a future where we are just, you know, entering these vehicles that move for us? No one said, you know, at the driver's seat or no one has their hand in the steering wheel. Is that not is that not going to happen?
So if you asked me a year ago, I would say definitely not. And the main reason why definitely not is because sooner or later, you have to communicate to a car what you want to do. And there are scenarios where it will be easier to just directly control the car than trying to explain to it or like click on something or like tell it where you want to go. It's like you go to a concert that's in a field and there's a person like waving a baton. Well, you're never going to teach a computer how to do that. So you're going to want to provide some sort of human instruction. What's changed is that in last year, you have large language models that come out that have actually made it a lot more practical to map sort of verbal, human intent into motion. And so I think you can get there, but it's not going to look exactly like how people see it right now. So right now you get your robot taxiing like you enter a destination and it's this very sort of scripted experience. And I don't think that that works for individually owned cars. Like you don't want to sit down in your car and then have to do a bunch of data entry before you get going. You want to sit down, you want to go. And then as you move along, you'll progress through different levels of autonomy.
So the way that we set it up is like if ever you like of the steering wheel, the car is driving. It doesn't have a very complex goal. Its goal is to like keep following the road and keep following the highway. But it's okay. The idea is that you're not displaying intent to drive. So the car fills that in. And you don't have to press a button and you don't have to set a speed. We just figure all that out from this surrounding traffic. And as a driver, as a driver, like I'm used to using adaptive cruise control in the highway, you know, it gets closer to the car, gets further from the car, breaks for me, simple. I love it.
How as a driver, a consumer, how would this be different for me on the highway?
作为一名驾车者和消费者,在高速公路上,这对我的影响会有何不同?
So for one thing, you wouldn't even turn it on. It's always on. So that's one of our philosophies is that your car is always smarter. You don't have to press a button to say, please be smart now. The other thing is that you don't set a speed. We know what the speed is. We actually survey all of the surrounding traffic. So you know, adaptive cruise control tends to be you go set speed until you approach another car and then you're locked into all of the car. What we did is we surveyed the traffic and we figure out the following distance and the speed. And so the intention is that you can go through a wide variety of driving scenarios. Like I often it's like, oh, you have a fast car and then you're in stop and go. And there's traffic that's close.
For us, our goal is that you don't make any adjustment through all of that. The car is figuring out how to adapt between those environments. So you're not changing the following distance. You're not changing the speed at all. And so we're getting people used to the idea that your car by default just does the right thing. If by default follows the road, if by default, we'll keep a reasonable following distance. All you have to do is nothing.
And so instead of the car just slowing down unless you press a button, it's going to keep driving along the road and sort of the simplest thing. And then what you do is you layer navigation on top of that. You say, I want to drive to this exit or I want to or maybe actually enter a destination at which point the car becomes more active in terms of changing lanes as well. And that's the goal by the end of this year is to do that navigation layer on the freeway.
How far do you think from having the first ghost equipped vehicle on the streets and not through your company? Obviously through a manufacturer or consumer? It's going to be the second half of this decade. So after 2025, like maybe 2026 to 2028. So that is the development cycle of cars. They want to make these decisions like two years before they actually trip. So that's about the time range that we think is the target. And what you see right now is the auto manufacturers are locked into what they're doing at least through 2025. And then it's kind of open. And the conversations we have with them say it's like, okay, we're on this level two path level two plus plus, but we want something more, but we don't know what that is yet. And different companies have organized themselves in different ways to try and answer that question.
Are you finding that certain manufacturers, whether and even splitting them up by domestic, Asian, European, are you finding that certain manufacturers are more receptive to conversations about this than others? Or is it just very, you know, just differs kind of brand by brand, not so much by where they're from in the world? It definitely matters where they're from in the world. So we're finding like the European manufacturers that do development in Silicon Valley are considerably more open than the ones that only do development in Germany. The American manufacturers, it's kind of the same thing where they're more open to the conversation. And what we found is that the better product they ship, the more reality they've been exposed to about how hard the next step is going to be, and the more open they are to a conversation.
Got it. So you're saying, as they're experiencing that, they're realizing that they need help solving this. So yeah, so you get this inverse behavior where the companies that haven't shipped any good features are usually harder to deal with because they haven't tried versus the company that shipped anything. It's like, you're talking like Ford and GM and Mercedes, who've done a lot of internal development, have a lot more experience with the problem. And so it's easier to have a productive conversation with them because they know where you actually run into roadblocks. And we can go directly to that part. Yeah, they felt the pain points. They're looking for the doctor.
I can't believe we missed this question, but why the name ghosts? We got there. It's a simple one. It's a simple one. So the inspiration is like the call of the Japanese commie, which is like, okay, what animates your car? We're not building a car. We're just making your car have intent and want to go somewhere. And that's the ghost in the car, that animates it. Nice. I love it.
Well, John, very eye opening in the world of autonomy. I think before we wrap up, I just give me a bit of macro. What is the self driving? Even for the, even if we're not self-driving, but what does the commute look like for the average person in like 2030? How is it different from today? The first thing that it'll be a lot less stressful. Like everyone, anyone who's done a long commute knows you get to the end of the commute and you're just tired from the commute. And so the first thing is like, if you can just, you know, sit back and like let the car ride itself, one thing I've noticed with my using the product myself is that usually I drive like probably like the top 5% in terms of speed, maybe the top 1%, depending on your measuring. And our car just goes slower because it's like kind of around the speed limit, but a little faster. And I find that I'm kind of okay with that. Like just because, you know, offloading into the to the car to do the driving just makes me feel a lot less stress.
We've done a lot of long test trips like all the way from recently we did San Francisco to Las Vegas and the stress has dropped off. And I think that one of the effects of that is going to be that people will be willing to commute a lot further than they would otherwise. And so we'll see if like eventually autonomy kicks off a new frontier of development where you can develop even further from workplaces because the commute is low stress enough that people will be willing to just go further in order to have more space and, you know, be in a community they prefer compared to where their job is. And on the tributus mentioned SF to Vegas, what was that like? Like what percentage of the time did you have to, you know, put your hands on the wheel? How did that work? It's almost never along that trip. The longest stretch we did without any intervention, I think it was about 120 miles. And the reason for that intervention is when you cross the border into Nevada, we have to change our license plate to go from a California registration to our Nevada registration.
But you can now do very, very long stretches without any intervention. This is going, there's tons of trucks around there. The road itself is pretty flat, but at times it gets pretty patchy. But the system is very consistent through that. And so we're spending a lot of time, not just on the long trips, but around Detroit where the highways are extremely variable to fix all those cases. And they're under construction because it's summer. Make sure we handle all those cases. Our goal is that you just never intervene and it never asked you to intervene under any circumstances. And you know, the car changing lanes on its own and everything. Yeah. Yeah, change lanes. Right now you indicate you tell it to change lane, but it's checking the side and checking the rear and the lane change occurs. And then the next step by the end of the year is to make that completely automatic.
Can this work in an environment where it's not perfect sunshine, cloudy, like, you know, there's a little rain, you know, something like that. Does that automatically kill it or what happens then? No, so cloudy is great. That's actually way easier than sunshine. So rain is fine. The main issue was the windshield wipers. The rain itself didn't seem to cause much disturbance on that on the lane markers, we've tested rain until like, you don't want to drive because the window is associated with water. The interesting things we're running into are glare. So think of a tunnel exit where there's like one bright light and then but the rest of the tunnel is dark. In Detroit, it's also dealing with salt spray is another issue because salt spray just creates lots of gunk on your windshield and on the lens by extension. And so those are the next challenges is to solve those cases. But you know, ordinary guy time light rain, you know, variable road conditions, glare on the road, we spent a lot of time this year solving for for glare where even people, I think, can't see where the lane markers are. Our goal is to be superhuman in all those respects.
I love it. Yeah, you're going to need little windshield wipers on the on the sensors because I can tell you I'm driving sometimes and it's like, Oh, I don't have my lost my sensors, rain is, you know, crazy rain or maybe there's some salt or whatever, something on it. Yeah, so we have it easy. We just put it behind the windshield. So it's the same windshield wipers. So same sensor. Nothing, nothing is outside the car. Nothing's on the roof. It's all inside the car. So if you can see system can see, it's great.
John Hayes, John, where can people learn more about you ghost? Where should people go? If they want to learn more. So our website is ghostatonic.com myself. I'm on Twitter at ghosthays, H-A-Y-E-S.
John Hayes, thank you so much. This is very fascinating. I'm going to be I'm going to be paying close attention where this goes. So I want to see, you know, I'm really curious to see how this evolves and I'm rooting for him. And I want to I want to see these on every car in the street. So this is going to be fun.
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