HIBT Lab! Nuro: Dave Ferguson

When you think about self-driving cars, you might imagine relaxing in the back seat while a vehicle carries you to your destination. But according to Dave Ferguson, nearly half of all car tips that Americans take don’t actually need any passengers at all. That’s because we spend a lot of our time driving around just to pick things up, like groceries and takeout. This week on How I Built This Lab, Dave talks with Guy about his vision of a future where many of these everyday errands could be done by robots. Dave’s company, Nuro, builds autonomous vehicles that are meant to deliver goods rather than carry passengers. Already they’ve run pilot deliveries with big-name partners like Domino’s Pizza, Uber Eats, and Kroger Grocery stores, and in the next few years, they aim to expand their service to cities all across the country. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

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• 0:00Guy Raz?

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• 0:46Guy Raz?

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• 4:23Guy Raz?

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• 5:07Guy Raz?

  Visit mobili fuels.com for details. Welcome to How I Built This Lab. I'm Guy Raz. So over the past several years, there has been a lot of progress and also a lot of hype around self-driving cars. There are several companies, like Tesla and Waymo and Cruise, all working to get more autonomous vehicles on the roads. And for most of these companies, the focus has been removing the driver from the car, which would allow passengers to relax without having to drive themselves. But what if you remove the passengers from self-driving cars as well? Well, that's the approach that our guest today is taking. His name is Dave Ferguson, and he's the co-founder of Neuro. It's a company that makes fully autonomous vehicles

• 5:50Guy Raz?

  that are made to carry goods, not people. And Dave imagines a world where many of our everyday errands, like grocery shopping, or food takeout, or package deliveries, could be performed by these cars. Already, the company's zero-occupant self-driving vehicles have been on the roads in Silicon Valley and in Houston, making deliveries with big-name partners like Domino's and Kroger grocery stores. Dave grew up in New Zealand, where he developed an interest in robotics during his time as an undergraduate at the University of Otago.

• 6:23Speaker 01

  This robot was this beautiful little red rubbish bin or trash can. It looked like a little mini Dalek from Doctor Who, but bright red. And and our task was to try to get it to map indoor environments. And so this was the first time that I'd ever interacted with a robot. I was totally hooked.

• 6:41Guy Raz?

  It was like a Roomba, it would just like move around the room and map it?

• 6:44Speaker 01

  Yeah, it was like a Roomba, but about a yard tall. Because back then, the sensors and the computer and everything was was very large to to be able to to navigate. And really, I fell in love with the idea of being able to provide a level of intelligence to another agent, and in particular, a physical agent, such that it could then go and make its own decisions in the world. Right? Like, we would, we would push a button and it would trottle along and it would basically decide whether it was gonna go into one room or another, whether it was gonna run straight into a wall or not, which unfortunately it did fairly often.

• 7:19Guy Raz?

  Yeah.

• 7:20Speaker 01

  But that but that autonomy was incredibly compelling for me. And and that started a pretty long, long love affair between me and fully autonomous robots. And so as I was finishing my undergrad, I was thinking about what to do next. And that same professor said, look, you should go to the robotics institute at Carnegie Mellon. You should go work with this particular professor. And you should go apply what you've learned to to bigger and even cooler robots there, which which is what I did.

• 7:48Guy Raz?

  Wow. So you end up at Carnegie Mellon, I think you're there from two thousand two to two thousand six, and you did your PhD there in robotics and and computer science. And and did you pursue that degree with presumably with the intention of working for, I don't know, a robotics company or or like a Google or something like that?

• 8:08Speaker 01

  Well, back then, that that wasn't really an option, quite honestly. I mean, when I was doing my PhD, I thought that I would be a professor. But, you know, I got that wrong many times. I originally thought I was gonna be a lawyer when I first went to university. That didn't work out. And so I thought that I was gonna be a professor. But as I was at CMU and I got more and more exposure into working on pretty big projects, like sending robots into mines and working on big outdoor robots. And then towards the end, these large, high-speed vehicles, I fell.

• 8:41Speaker 01

  More and more in love with the idea of of really applying robotics to to problems out in the real world. Now, unfortunately, at the time, there weren't a whole lot of jobs for roboticists that were finishing with a PhD. Right. And so the idea of going to work at a place like Google or or even a neuro today wasn't really a possibility. And so when I finished, I think what we did have, which was incredible, was an opportunity to work on these DARPA challenges. And and as I was finishing up my PhD, as you mentioned, in two thousand and six, the third DARPA challenge had just begun, which was this robot race in a mock urban environment. And so it was it was self driving vehicles.

• 9:22Speaker 01

  You had to obey traffic rules and regulations, and you had to interact with other self driving and human driven vehicles on roads. And it was a race to see who could do all of that, abide by all the rules and finish finish first. And so that was incredibly compelling for me. It was related to what I'd done for my PhD. And I sort of left it the opportunity to be a part of CMU's team for that competition.

• 9:46Guy Raz?

  All right. So you're part of this competition. And what do you do after you after you graduate? What I mean, you didn't obviously pursue academia. So what did you where did you go?

• 9:59Speaker 01

  So for that competition, I actually joined Intel. So Intel had a research lab they had just set up at Carnegie Mellon's campus. And the idea was that they wanted to have researchers that were keeping their fingers on the pulse of what was going on at the top academic institutions. And so they hired a bunch of really strong folks at that research lab. And when I was talking to them, I said, Look, I'm really excited about doing this urban challenge with the Carnegie Mellon team. I think it's going to be really, really exciting. And they said, Hey, that sounds great. Why don't you come work for us at our Intel Research Lab? And we'll effectively loan you to that team. And you can go work on this competition for the next year and a half. And then you can bring back some of what you've learned and and help work on some of the projects that we have going on in robotics.

• 10:43Guy Raz?

  So you were in Pittsburgh and I guess you also worked on this robot butler called Herb. This was like what was supposed to like get things for you and move around and.

• 10:53Speaker 01

  Yeah, yeah. So this was the personal robotics project at Intel. And yeah, the idea was to try to at least advance the state of the art towards what would be required to have a home robotic butler. And so, yeah, so we created Herb, which was short for the Home Exploring Robotic Butler. And it was it was a segue platform with a couple of robot arms on it. And the intent was for it to navigate around your home or workplace and tidy up. I think we spent about a year getting it to load and unload a dishwasher, which was a lot of fun. This was back in 2007, 2008, so a long time ago. And I think that a lot of the challenges that we that we faced with back then,

• 11:38Speaker 01

  particularly around manipulation, are still pretty thorny challenges today.

• 11:44Guy Raz?

  All right. So you were with Intel for a bit of time and then did you stay in Pittsburgh? What'd you do after that?

• 11:50Speaker 01

  After the urban challenge, I was honestly a little bit burnt out. I just felt like I could do with a little bit of a break. And I had a really, really good friend that was out in New York. And he said, look, it's really interesting out here, applying some of the techniques from machine learning that we've been working on as part of our PhD to the markets. I think you'd really like it. Why don't you come out and give it a go? And so I spent a few years out in New York and I worked for a hedge fund, basically trading using machine learning, which, you know, was it was really exciting. I think it's a it's a fun playground, the world of finance and automated trading. I think for me in the end, I just I didn't find that it sort of elevated my spirit enough.

• 12:35Speaker 01

  Maybe that's a diplomatic way of putting it. I just I missed working on something that I was truly, truly passionate about and that I felt really mattered for the world. Now, I mean, to be fair, a lot of the techniques that we apply in robotics are. Basically, taking in huge amounts of noisy data, trying to make sense of it, and then trying to come up with intelligent or hopefully reasonably intelligent actions. And all of that is very much on point for finance and trading. But, but yes, at some point, I just felt making one number bigger than another number was perhaps not what I had seen as my life's work, starting out my, my career in academia

• 13:17Speaker 01

  and beyond. And so I was drawn back to robotics and ended up coming back out to work with some of my friends that I had known from CMU that were now at Google, working on the self-driving car project. So this is in 2011.

• 13:30Guy Raz?

  Got it. And, and tell me about what you were tasked to do when you got to Google?

• 13:36Speaker 01

  So when I got there, the team was about 12 people, and it was an incredible team. As I mentioned earlier, there were so few opportunities really to work on applied robotics out in the real world, and in particular to work at a company as strong as Google.

• 13:55Speaker 01

  And, and so when I got there, I actually worked on, on the prediction system. So this was trying to predict what other agents, other road users were going to do. And so this was some of the first machine learning that, that we incorporated into the self-driving car project at Google. Now, obviously, sort of all of our systems are incredibly heavily machine learning based, but, but back then it was, it was relatively new. And so it was just an opportunity to work on brand new tech as well as obviously this application that, that was super compelling to all of us with, with a small, incredibly strong team.

• 14:34Guy Raz?

  And I guess while you're on this team, which initially was a small team, you meet the guy who would eventually become your co-founder for Neuro, Jiejun Xu, and, and he, he had already been working on the project for a few years by that point?

• 14:49Speaker 01

  Yeah, Jay-Z joined right at the start. So in 2009, the project started and Jay-Z was one of the very first engineers. He had been at Google. He was working on Google Maps and he got pulled in to to help seed that self-driving car team. And so when I, when the two of us were there and we worked together for about five years at Google before starting Neuro, he managed the perception team and I managed our machine learning, behavior prediction, computer vision, and scene understanding team. So our teams were very closely intertwined. We, we had a lot of collaboration and we worked very closely together. In fact, the two of us have been literally sitting next to each other for, for over 10 years now.

• 15:29Guy Raz?

  And, and this project is basically what eventually became Waymo, right? I mean, that's what we now call Waymo began as this self-driving project that you guys were on.

• 15:39Speaker 01

  That's right.

• 15:41Guy Raz?

  All right. So you, I think you're there for about four or five years at Google and the two of you, you and Jay-Z decide to, to start your own autonomous vehicle company. Tell me how, how you guys, I mean, obviously you're working around self-driving vehicles, but what did you want to do? What was, what was going to be different about what you guys wanted to pursue rather than what you already were doing at, at Google at that point?

• 16:05Speaker 01

  We, we saw an opportunity for robotics in general. You know, when we created Neuro, it really, it wasn't and isn't a, a self-driving company, nor a self-driving delivery company. It's really a, a general robotics company. And what we saw was, if you look back the last several decades, maybe the last 30 years, our, our relationship with the digital world has completely transformed. I mean, even the internet is basically within the past 30 years, right? And then smartphones and, and our digital connectivity and consuming content and all the rest. But if you look at how our relationship to and with the physical world has changed, it's largely very similar. And what we felt and what we still believe is that Over the next 20 to 30 years, we're going to see a pretty significant

• 16:50Speaker 01

  transformation in how we interact in the physical world. And then we think it's going to be because we're going to see the advent of really useful, really beneficial, physical devices that are going to come and and make our lives a lot better. And so we wanted to create a company that would help accelerate that transition. And so our mission for the company was to to really use robotics to better everyday life. And so we we decided it was the right time to start a company in that space. When we started Neuro, we didn't know exactly what application we're going to work on. And so the two of us spent a bunch of time around whiteboards, thinking about all of the possible applications of robotics that might be somewhat feasible.

• 17:31Speaker 01

  And in the end, we we settled on transforming local commerce through self-driving delivery. And and the reason for that was that it was a massive, massive societal benefit. Almost half of all personal vehicle trips that we take today are for shopping and running errands. So that's almost 100 billion trips every year just in the US.

• 17:51Guy Raz?

  Wow.

• 17:51Speaker 01

  That frankly, we can replace if we had a a service that could bring things to you without you having to to drive around and and all of the associated impact in a negative sense from from doing that.

• 18:03Guy Raz?

  Yeah.

• 18:03Speaker 01

  And it was a huge market, right? Those 100 billion trips represents a massive scale and and an opportunity to give people time back, to reduce emissions, to strengthen local communities, to reduce food deserts. You know, every angle that we looked at it from, it it seemed like a really compelling, really worthy opportunity for us to go after.

• 18:27Guy Raz?

  We're going to take a quick break. When we come back, more from Dave Ferguson on how Neuro is building self-driving vehicles for delivering everything from pizza to packages. Stay with us. I'm Guy Raz and you're listening to How I Built This Lab.

• 18:42Guy Raz?

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• 22:18Guy Raz?

  Welcome back to How I Built This Lab. I'm Guy Raz. My guest is Dave Ferguson. He's a co-founder of the self-driving delivery vehicle company, Neuro.

• 22:28Guy Raz?

  All right, so you basically decide to launch this company. This is not a cookie brand. This is going to require massive, massive amounts of money. And indeed, you raised, about two years in, $92 million in a Series A round.

• 22:49Guy Raz?

  Tell me a little bit about what the sort of the building blocks were to make this come to life. It was you and Jay-Z and then presumably you had to build a facility to start to construct these vehicles. Tell me, just kind of unpack the architecture of how you kind of did this initially.

• 23:09Speaker 01

  Yeah, well, the next one will definitely be a cookie company guy. This is, it's been a lot. It's been a lot the last six and a half years. So when we started, we were actually in an Airbnb. It was very HBO Silicon Valley style. And we had sort of one room for each team. So we had our software team in one room, a hardware team in one, our product team in another. We had wires going through the house up to where the washing machine was so that we could get 240 volts to charge the electric vehicle. And so it was, I mean, it was very high energy, I think, very exciting time. But we had to show some things before

• 23:50Speaker 01

  we were able to get the traction that we did with investors. And so our goal was to try to get an initial prototype up and going. And to do that, we had a Nissan Leaf that we converted into a self-driving vehicle. And within sort of the first six months of the company, we had it driving around reasonably well, the neighborhood. And then in parallel, we also worked on designs for what a custom goods only vehicle would look like. And that for us was a pretty big aha moment, because it turns out that if you can relax the constraints for an on-road vehicle to not have to put people in it, then in many ways, you can almost entirely rethink what vehicle design is. And in particular, you can make a lot

• 24:35Speaker 01

  of safety optimizations for the vehicle itself that largely significantly improve safety of other road users. So one of our, one of the mottos that we have internally is that we want to keep what's outside even safer than what's inside. And so everything from external airbags to external crumple zones are pushed towards this. And so that first vehicle we worked on the design for, and in the first year of the company, we had our very first vehicle. We called it the R1. You know, it was an initial prototype. And it was a great showcase for what would be possible.

• 25:10Guy Raz?

  And just to describe this, it's the size of like a one of those Fiat cars, those 500s with these sort of doors that open up on the sides. And inside you would find your groceries or whatever, whatever, you know, might be delivered to you. These cars are autonomous, there's no steering wheel, they're self-driving, but presumably they can be operated remotely for safety, right?

• 25:32Speaker 01

  They can. We have remote operators, we call them guardians, that monitor the vehicles. You know, we try to be very careful about ensuring that any vehicles that we're operating out in the wild, in the public, that we have really robust monitoring. And we can send commands to the vehicle. We can tell the vehicle, for instance, hey, pull over or, you know, be cautious. We can also answer questions for the vehicle. In limited scenarios, we can drive the vehicle very slowly when the autonomy system, for whatever reason, needs some help.

• 26:06Guy Raz?

  And I guess this is a vehicle that is unique in many ways. And one of the ways it's unique is that it has an exemption from certain government agencies. Understandably, most cars have to have steering wheels and pedals and side view mirrors to be street legal. And your vehicle is the first one that is exempt from any of these requirements.

• 26:32Speaker 01

  Yeah, that was actually our second generation vehicle. So a couple of years ago, we got that exemption for the vehicle that we are today actively operating out in California and Texas. But you're absolutely right. The federal motor vehicle safety standards right now, you know, it's a 50-odd-year-old piece of legislation that defines what a vehicle is and what requirements need to be there. And it makes an enormous amount of sense if you assume that there's always a person inside a vehicle driving it. When you no longer have that reality, a lot of the stuff doesn't make so much sense, like steering wheels and side mirrors and even windshield wipers. And so we've been working with the Department of Transportation since basically the start of the company.

• 27:16Speaker 01

  And so they've been very supportive and that was part of what led to us getting that exemption so that we could operate our second generation vehicle.

• 27:24Guy Raz?

  All right. So the idea from the beginning was to design vehicles that would carry goods and really to replace, as you say, most of the trips that we take to the grocery store or for small errands to go pick things up, which could be replaced by an autonomous self-driving vehicle.

• 27:44Speaker 01

  That's right. That's right. It's almost half of all trips that we take, which is an enormous opportunity, right? If you think about it, and that works out to roughly 150 hours a year, Guy, that on average every American is spending on those trips. And so if you think about it, that's roughly half an hour a day that you could get back if you had a service that could do that for you, not to mention the safety and the fact that a lot of those trips are driven in a Ford F-150 to go get milk from your local grocery store. So there's a huge, huge environmental impact and improvement on the emission side that we can do. There's also accessibility, you know, over 20 million people in the US live in food deserts, which we think we can make a significant dent in if we're able to provide

• 28:29Speaker 01

  this service across all, across all neighborhoods and cities. And so there's, there's a lot. There is a pretty massive opportunity if, if and when we can get this right and build out a service that can provide this delivery.

• 28:42Guy Raz?

  I know you did a partnership with Kroger. I think Kroger's the second or maybe the biggest grocery chain in the US. This was presumably a pilot, but what, how did the pilot work?

• 28:56Speaker 01

  Yeah. So, so we worked with Kroger and we'd been working with Kroger for the last five years, pretty, pretty consistently doing delivery services with them. And first it was in Phoenix where we did this first pilot with the R1. And the idea was that Kroger customers could order delivery from their local Kroger. It was actually a Fries, which is owned by Kroger, the Fries grocery store out in Scottsdale. And if they lived within a certain region around that store, they would be eligible for it to be delivered by our R1 vehicle. And so we were doing active deliveries and I think we did a few hundred, a few A few hundred deliveries with the R1 to the general public around that fries.

• 29:39Speaker 01

  And it was, you know, it was a great opportunity for us to to learn what it takes to actually operate a small but real delivery service and to get feedback from both our partner Kroger on the loading experience and and what that looks like as well as from end consumers on on what the interaction and the the user interface on the delivery side looked like. So that was really exciting for us. That was back in the end of, I think that was the end of 2018, early 2019 that we did that. And, you know, I think ever since we've continued strength, certainly strengthening our relationship with Kroger, with whom we have a big sort of long term committed partnership now,

• 30:21Speaker 01

  and also learning from it how we wanted to improve the overall product. And that led to some of the changes that we made in our second generation and now third generation vehicles.

• 30:32Guy Raz?

  All right. So now, as these vehicles start to come online, right, tell me, help me understand how they operate. I mean, we've had, as you know, we've had Cruise on on the show, which operate autonomous passenger vehicles for human passengers. And people are familiar with like Tesla self driving vehicles, which are mainly cameras that navigate the vehicles. How how do your vehicles work? How are they able to navigate roads safely?

• 31:03Speaker 01

  Yes, our vehicles are fully driverless. I mean, there's no, there's no question there because there's no, there's no space to have anyone inside them. So they're doing everything entirely autonomously, entirely on their own. They they use a bevy of sensors, you know, somewhat similar to to Cruise and Waymo, where we have cameras, we have lidars, we have radars, we have thermal cameras as well to help detect people and other living beings at night in particular. And they take all of the sensor data, they make sense of the world from that data, and then they figure out what's what's the right move for them to make. Now, one of the differentiators for us,

• 31:44Speaker 01

  because we're only moving goods around, is that we get to lean a little bit more heavily on to the safety side of fully autonomous operation as opposed to the comfort side. And so, one of the reasons why self driving is so, so difficult a challenge is that you have very little room for So on the safety side, you have to make sure that your vehicle is not going to hit anything. But at the same time, you have the comfort of the passenger that is inside the vehicle for sort of passenger-based self-driving vehicles. And so you have to both be safe, which would generally bias your system towards trying to be conservative, like slow down if you think you've seen something. But when you're in that vehicle, if it suddenly slows down or acts a bit too conservative,

• 32:29Speaker 01

  you look out the window and you see nothing there and you say, hey, this, I'm losing some trust in this.

• 32:34Guy Raz?

  Yeah.

• 32:34Speaker 01

  Now, when you remove passengers, you still have to nail safety. But like our, our groceries don't care if we're a little bit more of a defensive driver than you or I might want our driver to be. We're okay with taking our foot off the gas if we think we've seen something until we get enough additional sensor measurements to get confidence that, okay, there's actually nothing there. Now we can put our foot on the gas again. And that means that we can, we believe, do a really, really fantastic job from a safety perspective and still be able to get a system that we're able to deploy out into the real world much faster because we don't have to be worried as much about the comfort side.

• 33:15Guy Raz?

  Hmm. I know, I mean, you, you guys have done partnerships with, as you mentioned, Kroger and Domino's Pizza and Uber Eats. But right now, they're, it's very limited. They're in very limited markets and very small areas in those markets. I'm not, it's not a criticism, it's just, it's just the, it is what it is. What are the hurdles? I mean, why, tell me what you have to do to make this available everywhere? Is, is the technology still not quite there yet? I mean, or, or do you feel confident that right now, if you got the approvals from, from various regulatory agencies, you could start to deploy these neuro vehicles all over the country and they would operate perfectly?

• 33:58Speaker 01

  There's a few things that have to sort of go in lockstep. I would say it's still largely about the supply side. And so the supply side is effectively both having vehicles at scale, mass manufactured, tens or hundreds of thousands of them rolling off the line so that we can truly scale across the US and beyond.

• 34:17Guy Raz?

  And now you probably can only, because they're custom made, so probably can only make maybe 1,000 or 500 a year at most.

• 34:23Speaker 01

  Well, so we're working with BYD, who is, they usually alternate between Tesla as the number one or number two electric vehicle manufacturer in the world. I think right now they're number one. And so we do have the capacity or will have the capacity to make hundreds of thousands of those a year. Yeah, so that's, that's one side. And there's also the autonomy supply side. And so that's effectively getting our autonomy system to be able to operate in a large enough set of areas. And if you look at how Neuro is expanding, it's relatively similar to other leaders in the space, where we're sort of looking at areas where the weather is, is quite forgiving for self-driving vehicles. It's not that we can't solve the challenges of snow

• 35:08Speaker 01

  and really difficult weather conditions. It's just that we would like to scale a service and get to commercial viability before we have to solve that. And we're feeling really good about it. I mean, we have regular operation, fully driverless custom vehicles in both the Bay Area and in Houston. And we're constantly expanding the regions over which we're operating. And so, so we're making a lot of progress on both of these fronts. But really, it's those two coming together over the next year or so for us to be able to provide a, a commercial service over a pretty significant region and then going on to, to really turn on the spigot of the manufacturing and then scale it across the country.

• 35:52Guy Raz?

  We're going to take another quick break, but we'll be back in just a moment with more from Dave Ferguson, co-founder of Neuro. Stay with us. I'm Guy Raz and you're listening to How I Built This Lab.

• 36:12Guy Raz?

  Welcome back to How I Built This Lab. I'm talking with Dave Ferguson. He's the co-founder of Neuro. It's a self-driving, fully autonomous vehicle company that focuses on delivering goods.

• 36:25Guy Raz?

  Tell me a little bit about, as I mentioned earlier, to build a company like this requires tons and tons of money. I think you've raised about a bit over $2 billion. And you've got your own track, right? Your own closed track to test your vehicles on. And are you also building some of this machinery yourself? I mean, I know you mentioned BYD in China, but do you have a facility where you're actually building the vehicles or the prototypes?

• 36:53Speaker 01

  Yeah, so as I mentioned, we're on our third generation. And on all three generations, we have really designed or co-designed the vehicle. And so if we take the third generation, the Neuro, as an example, we designed the entire electrical system, we designed a lot of the safety systems, and all of the sensing systems. And in fact, as we assemble those vehicles, their final assembly will be done in the US, first at a Lancaster facility in California, where we'll put the chassis together, effectively the vehicle part.

• 37:27Guy Raz?

  And I think Lancaster is where BYD has a facility in the US.

• 37:30Speaker 01

  That's correct. It will be at that facility. You're exactly right. And then we will take that chassis to Vegas, to one of our Neuro sites there, and we will do all of the final assembly of the sensing and the compute, basically the brains and the eyes and the ears of the vehicle. And so all of those sensor assemblies individually, we do ourselves. And then the assembly of all of those components onto the vehicle, we'll do ourselves as well. So there is a fair bit of in-house manufacturing that we'll be doing, in addition to the chassis final assembly, all in the US.

• 38:03Guy Raz?

  So the Neuro 3, that's now the latest iteration, will that be the one that is the main consumer-facing delivery vehicle? Or do you think by that time, by the time you really scale, you're going to be on Model 4 or 5 or whatever?

• 38:20Speaker 01

  No, that'll be it, Guy. I hope that's the one that you'll be able to get your produce for preparing your meals. I know you're a big cook. We hope that that's the one that we'll be able to scale across the whole country. Now, that is very much a... Optimized vehicle for goods transportation. Now, you know, that is, that is absolutely our focus. It's what our bread and butter is. It's, it's what our sort of raison d'etre is for, for a company for the first application. You know, longer term, there may also be opportunities to expand into perhaps vehicles that also transport passengers. But for us, you know, we, we want to stay very, very focused. I think focus is one of the superpowers of a startup. It's one of the, the real advantages that we have.

• 39:03Speaker 01

  And the opportunity and the impact of what we're doing in a goods, purely goods delivery is just so huge. Uh, I think we want to stay very, very targeted and really nail that application.

• 39:16Guy Raz?

  What, what happens, Dave, when, you know, inevitably one of these vehicles gets hit? Not to say that the vehicle, it's the vehicle's fault because I think the technology is, is very good and I've, I've been in, in some of these vehicles and I, I'm pretty confident in them, but you know, other human driver might side swipe it or might topple over or, um, you know, somebody might decide to just vandalize it. How do you respond to those kinds of scenarios?

• 39:44Speaker 01

  I think there are, there are a couple of factors or challenges at play. So one is first ensuring that the system can detect that something has happened and bring itself to a safe state. And so effectively detecting that a collision has happened or some dangerous situation, and then making sure that it pulls over and it stops. Uh, the second is what do you do after that, right? Like, how do you, how do you interact with law enforcement? How do you make sure that, uh, that anything that has happened, you're, you're able to potentially recreate and understand what actually went down and, and whose fault was it? And are there things that we can improve on the software side? I think one of the benefits that we have is that our vehicles are designed to have

• 40:25Speaker 01

  a very easy, uh, user interface and interaction with people outside the vehicle. So we have a very large touchscreen. We have bi-directional video cameras. And so everything that we use to make a really delightful seamless experience for someone getting a package from the vehicle can also be. Be used by, for instance, law enforcement for communicating with our mothership and our monitors and getting any information that they want. And so we intend to make use of that. And we have, you know, we've published some of the law enforcement interaction plans for how to interact with our vehicle. But we do think that there's a pretty nice opportunity there to do a really good job of that,

• 41:08Speaker 01

  because we have to do a good job of that anyway, just for our core product.

• 41:12Guy Raz?

  So this is unrelated to the technology, but of course, related to the economic environment that we are now presumably entering. Neuro, like many other technology companies in the Bay Area has undergone some layoffs. What do you, I mean, how do you sort of envision, you know, the next 12 months affecting your business? If at all?

• 41:33Speaker 01

  Well, we've, you know, we did, we did go through layoffs and, you know, that's really a pretty awful situation, you know? Jay-Z and I have often said that the building the neuro team is what we're most proud of. And here we were having to cut roughly 20% of it. And that was all on us for growing too aggressively and being too optimistic about the market and funding conditions. And I think what we're seeing is that we are in a sustained, fairly challenging period for the market and correspondingly for funding for very hard tech companies, right? We are a company that is doing some, some pretty crazy things. We're very excited about it and I think we're making a lot of progress.

• 42:15Speaker 01

  But, but there's hard technology at the heart of this and that requires significant investment before it breaks through to profitability and then is a massive, massive business. And so we are trying to be very, very thoughtful about how we manage our burn as a company, where we spend every dollar and how we ensure that with the balance sheet that we still have, you know, we still have roughly a billion dollars on the balance sheet, that we can get to a place where we have largely de-risked all of the key risks for us, both in terms of the technology and also scaling and the demand with our partners, and are in a really, really strong position, you know? We generally We feel really, really good about where the company is.

• 42:57Speaker 01

  The layoff was something that was the most painful decision that we we had to make. And and honestly, from a personal perspective, it it's really the worst because with other hard situations that we've gone through as a company. Generally, Jay Z and I can be in the thick of it and we can try to shoulder as much as possible. You know, we're in the trenches with the team and we sort of make sure that we're taking as much fire as anyone else. But with layoffs, you don't get to do that. The reality is that it's folks that are laid off that are the ones that are suffering the consequences of our mistake. And so, you know, it it's on us to to really learn from that and sit with it. And then and then to remember why we're doing this and to get on with it and to try to honor all of those people that have contributed to Neuro, those that are still with us and those that aren't,

• 43:42Speaker 01

  to really try to succeed in this mission because at the end of the day, we genuinely believe it matters. That's why we're here and really want to go and realize it and nail this for for everyone that has ever contributed.

• 43:56Guy Raz?

  Yeah. So let's go sort of 10 years into the future now, right? And there are obviously competitors to know there are other companies who are working on this kind of technology. But in 10 years from now, if most people have access to these fully autonomous self-driving vehicles that can deliver things, what are we what are we talking about? It pulls up to your house, you walk out and you get your groceries, your pizza, food deliveries. Is that what we're talking about mainly?

• 44:24Speaker 01

  Yeah, I think that that's the first step. I think as as we're able to provide these on-demand services such as your dinner to you and dramatically reduce the cost of them such that they're affordable to everyone. And we can really eat away at those 93 billion odd trips that people are taking that frankly, in our minds are pretty unnecessary. As we build a service that does that, I think there are a number of opportunities to add additional really valuable and we think really exciting products for for customers. So one one example is packages. So right now, I mean, most of us Get umpteen packages delivered from Amazon, FedEx and others.

• 45:07Speaker 01

  And there's a challenge associated with trying to do that with a self-driving vehicle, because most of the time we get packages delivered, we're not home. And we don't want to be home, frankly. We want the package to come and get left on our doorstep. If you have a self-driving vehicle, it's harder for it to leave it on your doorstep. You know, we considered slingshots and drones and other things that could take it from the vehicle to your front door, but as of yet, that's fairly challenging. And so what we see as the long-term future is if we can replace these trips that you're taking, and the enormous number of those, and you end up having a service that's coming to your house pretty regularly, either it's bringing you dinner, or it's bringing you toiletries,

• 45:52Speaker 01

  or emergency goods, or groceries or whatnot. When that vehicle shows up with your dinner, for instance, it can also bring whatever packages have come for you, right? And so we do see an opportunity where you can start batching different services. And effectively, as an end consumer, you're paying the cost of meeting the vehicle once, but you're getting all of the items that you might want delivered at the same time. And that's what I think genuinely is the future of package delivery. It's that the packages are going to effectively come along for the ride with another on-demand delivery that you are going to get anyway. And I think that's the best possible end consumer experience.

• 46:36Guy Raz?

  That's Dave Ferguson, co-founder of Neuro. Dave, thanks so much.

• 46:40Speaker 01

  Thanks, guys. It's been a pleasure. Really appreciate it.

• 46:44Guy Raz?

  Hey, thanks so much for listening to How I Built This Lab. Please do follow us on your podcast app so you always have the latest episode downloaded. If you want to follow us on Twitter, our account is at How I Built This, and mine is at Guy Raz. And on Instagram, I'm at Guy.Raz. If you want to contact the team, our email address is [email protected].

• 47:08Guy Raz?

  This episode was produced by Chris Messini with editing by John Isabella. Our audio engineer was Andy Huether. Our music was composed by Ramtin Arablouei. Our production team at How I Built This includes Alex Chung, Carla Estevez, Casey Herman, J.C. Howard, Liz Metzger, Sam Paulson, Kerry Thompson, and Elaine Coats. Neva Grant is our supervising editor. Beth Donovan is our executive producer. I'm Guy Raz, and you've been listening to How I Built This.