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HIBT Lab! Nuro: Dave Ferguson

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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's several companies like Tesla and Waymo and Cruz 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. 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 NURO.

It's a company that makes fully autonomous vehicles 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. This robot was this beautiful little red rubbish bin or trash can. It looked it looked like a little mini Dalek from Doctor Who, but 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. Um I was totally hooked. It was like a roomba, it would just like move around the room and map it? Yeah, it was like a roomba, but about um 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 then it would trotle 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. Yeah. Uh, but that but that autonomy was incredibly compelling for me and and that started a pretty long, long uh 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. uh you should go work with this particular professor, um and you should go apply what you've learned to to bigger and and even cooler robots there, which which is what I did. Wow. So you end up uh 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 in intention of working for I don't know, a a robotics company or or like a a Google or s something like that? Well, back then that that wasn't really an option, quite honestly. I mean when when I was doing my PhD, I thought that I would be a professor. Um, but uh you know, I got that wrong many times. I originally thought I was gonna be a lawyer when I first went to university, uh and that and that didn't work out. Um 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 I fell 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, um 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 as I was finishing up my PhD, as you mentioned, in 2006,

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

after you graduate. What it w I mean, you didn't obviously pursue academia, so what did you Wh where'd you go? So for that competition, I actually joined Intel. So Intel had a research lab they had just set up at Kagi 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 uh with the Carnegie Mellon team. think it's gonna 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. Uh 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.

Um so so you were in Pittsburgh and and I guess you you also worked on this this robot Butler called Herb. This was like what we was supposed to like get things for you and move around and Yeah, yeah. So 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 a home robotic butler. Uh and so yeah, so we created Herb, which was uh short for the home exploring robotic butler. And it was it was a Segway platform with a couple robot arms on it. And the intent was for it to

navigate around your home or or workplace and and tidy up. I think we spent about a year getting it to load and unload a dishwasher, uh which which was a lot of fun. Um this was yeah back in two thousand seven, two thousand eight, so a long time ago. And and I think that a lot of the challenges that that we uh that we faced with back then, or particularly around manipulation, uh are still pretty thorny challenges today. Mm All right, so you y you were with Intel for um a bit of time and then did you stay in Pittsburgh? W what'd you do?

After that. 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 uh 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 uh out in New York and I worked for a hedge fund basically trading um using machine learning, which you know it was it was really exciting. I think it's a it's it's a fun

playground, uh, the world of finance and and automated trading. I think for me in the end, I just I I didn't find that it sort of elevated my spirit enough. You know, 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 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 I just felt making one number bigger than another number was perhaps not what I had seen as my life's work uh starting out my my career in in academia and and beyond. And so I was drawn back to robotics and and ended up coming back out to work with some of my friends uh that I had known from CMU that were now at Google working on the self driving car project. So this is in two thousand and eleven. Got it. Um, and and tell me about what you were tasked to do when you got to Google.

So when I got there, the team was about twelve people, uh, and it was an incredible team. Um as as I mentioned earlier, there were so few opportunities really to work on applied robotics uh out in the real world. And in particular to work at a company as strong uh as Google. Um 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. Um and so it was just an opportunity to work on brand new tech as well as um obviously this application that that was

super compelling to all of us with with a small, incredibly strong team. And and I guess w while you're on this team, which initially was a small team you meet the guy who would eventually become your co founder for for neuro um Judge in Zoo. And and he he had already been working on the project.

For a few years by that point. Yeah, Jay Z joined right at the start. So in two thousand and nine the project started and Jay Z was one of the very first engineers. He had been at Google. Uh he was working on Google Maps and he got pulled into 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 Neura,

He managed the perception team and I managed our machine learning, behavior prediction, computer vision, uh and scene understanding team. So our teams were very closely intertwined. We we had a lot of collaboration, um and we worked very closely together. In fact, the two of us have been literally sitting next to each other for uh for over ten years now. And and this project is basically what eventually became Waymo, w right? I mean that that's what we we now call Waymo began as this self driving project that you guys were on. That's right. Um all right, so you I think you're there for about

At Google. And the two of you uh 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 gonna be different about what you guys wanted to pursue rather than what you already were doing at

And Google at that point. We we saw an opportunity for robotics in general. Yeah, when we create a neuron it 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 thirty years, our our relationship with the digital world has completely transformed. I mean i even the internet is basically within the past thirty years, right? And then smartphones and and uh 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 twenty to thirty years we're gonna see a pretty significant transformation and how we interact in the physical world. And we think it's gonna be because we're going to see the advent of really useful really beneficial physical devices uh that are gonna 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 uh for the company was to to really use robotics to better everyday life. Um, and so we we decided was the right time to start a company in that space. When we started Neuro, we didn't know exactly what application we were gonna 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. 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 a hundred billion trips every year just in the US. 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 uh impact in a negative sense from from doing that.

And it was a huge market, right? Those hundred 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 uh opportunity for us to go after it. We're going to take a quick break when we come back more from Dave Ferguson on how Nuro is building self-driving vehicles for delivering everything from pizza to packages.

Stay with us. I'm Guy Roz and you're listening to How I Built This Lab. 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 NURO. Alright, so you you basically decide to launch this company. This is not um, you know, a cookie brand. Um

It's this is it's gonna require massive, massive amounts of money. Um and indeed u you you raised but two years in, ninety two million dollars um in a series A round. Um Tell me a little bit about w what the f 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. Uh t tell me how just kind of

Unpack the architecture of of how you kind of did this initially. Yeah, well the next one will definitely be a a cookie company guy. Um this is uh it's been a lot. It's been a lot the last six and a half years. Um so so when we started, we were actually in an Airbnb. It was very HBO Silicon Valley style. Um and we had sort of one room for each team. So we had our software team in one room, a hardware team in one, um, our product team in another, we had uh wires going through the house, uh up to to where the washing machine was so that we could get two hundred and forty volts to charge the electric vehicle and so it was I mean it was very high energy, I think very exciting time. Uh, but we had to

show some things before we were able to get the traction that we did uh with investors. And so our 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 um 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 onroad 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 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, um are are pushed towards this. And so that first vehicle we we

worked on the design for and in in the first year of the company, we had our very first vehicle. We called it the R One. You know, it was an initial prototype. And it was a great showcase for what would be possible. And just to describe this, it it's the size of like a f one of those fiat. cars, those five hundreds. With with these sort of doors that open up on the sides and inside you would find your groceries or whatever whatever it 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? They can. We we have remote operators, we call them guardians, that that monitor the vehicles. Um uh you know, we we try to be very careful about ensuring that any vehicles that we're operating out in the in the wild uh in the public that we 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. Um we can also answer questions for the vehicle in limited

scenarios we can drive the vehicle very slowly um when the autonomy system for whatever reason needs some help. And I guess this this is a v a a vehicle that is um unique in in many ways. It's unique is that it it has an exemption. From Certain government agencies.

Understandably most cars have to have uh steering wheels and pedals and side view mirrors to be street legal. And your vehicle is the first one. That is exempt from from any of these requirements. 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 in California and and Texas. But you're absolutely right.

the federal motor vehicle safety standards right now. Yeah, it's a Fifty odd year. uh old piece of legislation that defines what a vehicle is and 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. Uh when you no longer have that reality, a lot of the stuff's make so much sense, like steering wheels and side mirrors and even windshield wipers. And so We've been working with Department of Transportation since basically the start of the company and and so they've been very supportive and and that was part of um what led to us getting that exemption so that we could operate our second generation vehicle.

Alright, so the idea from the beginning was to design vehicles that would carry goods And 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. 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 and that works out to roughly a hundred and fifty hours a year, guy, that that uh on average every American is spending On those trips. And so if you think of that, you know, 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 one fifty to go get milk from your local grocery store. So there's a there's a huge um huge environmental impact and improvement on the emission side that we can do.

Uh, there's also accessibility, you know, over twenty 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 this service uh across all uh across all neighborhoods and cities. So there's there's a lot. There it's a pretty massive opportunity if if and when we can get this right, uh and build out a service that can provide this delivery. I I know you s you did a partnership with Kroger, the I think Kroger's the second or maybe the biggest grocery chain in the US. Um This was pr was presumably a pilot.

But Wha how d how did the pilot work? Yeah, so so we worked with Kroger and we've been working with Kroger for the last five years, um pretty pretty consistently, uh doing delivery services with them. And uh at first it was in Phoenix where we did this first uh pilot with the R one. And the idea was that Kroger customers could order delivery from their local Kroger. It was actually a Fry's, which is owned by Kroger, um, the Fry's grocery store out in in Scottsdale. And if they lived within a certain region around that store, uh they would be eligible for it to be delivered by our R one vehicle. And so we were doing active deliveries and I did I think we did a few hundred, uh a few hundred deliveries with with the R one to to the general public around that prize. And it was you know it was a great opportunity for us to

to learn what it takes to actually operate. a 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 in 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 uh the end of I think that was the end of twenty eighteen, early twenty nineteen, uh that we did that. Um And

you know, I think ever since we've continued strength certainly strengthening our relationship with Kroger, uh, with whom we have a big sort of long term uh committed partnership now, 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. Um all right. So now as these vehicles start to to come online, right? it help me understand how they operate. I mean Um we've had

Uh as you know, we've had uh crews on. on the show uh which operate autonomous ve passenger vehicles for human passengers And people are familiar with like Tesla self driving vehicles, which are mainly cameras uh that navigate the the vehicles. How How do your vehicles work? How are they able to navigate roads

Safely. Yeah, so 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 uh 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 Cruz and Waymo, where we have cameras, we have lidars, we have radars, we have thermal cameras as well to help detect people and and other living beings uh at night in particular. And they take all of the sensor data, they make sense of the world uh from that data, and then they uh figure out what's what's the right move for them to make. Now one of the differentiators for us

Moving goods around. is that we get to lean a little bit more heavily onto 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 to challenge is that you have very little room for error. So on the safety side, you have to make sure that your vehicles is not gonna 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-driven vehicles. And so you have to both be safe, which would generally

uh 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, you look out the window and you see nothing there and you say, Hey, this I've I'm losing some trust in this. Yeah. 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. I know I mean you you guys have done um partnerships with as you mentioned Kroger and Domino's Pizza and and Uber Eats. But right now they're it's very limited. They're in 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 w 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 neur vehicles. all over the country and they would operate Perfectly.

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. And now you probably can only'cause they're custom made, so probably you can only make maybe a thousand or five hundred a year at most. Wow, so we're working with BYD, um, 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 w we do have the capacity or will have the capacity to to make hundreds of thousands of those a year. Yeah. So so 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 how neuro is expanding, it's 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 and really difficult weather conditions. It's just that we would like to scale a service and get to commercial uh viability before we have to solve that. And we're feeling really good about it. I mean we have uh regular operation, fully driverless custom vehicles in both uh 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, uh, 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 uh spigot of the manufacturing and then scale it uh across the country. We're gonna 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. 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.

Um Tell me a little bit about as as I mentioned earlier, I mean to to build a company like this requires tons and tons of money, I think you've raised about a bit over two billion dollars. Um, and you've got your own track, right? Your own a closed track to test your vehicles on and do you also Are you

Building some of this this machinery yourself. I mean I I know you mentioned BYD in China, but I mean, do you have a facility where you're actually building the vehicles or or or the prototypes? Yeah, so we've w as I mentioned we're on our third generation and on all three generations we have have really designed or co designed the vehicle. And so if if we take the third generation, the the neuro, uh 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 at a Lancaster facility in California where we'll put the chassis together, effectively the the vehicle part. And then I think Lancaster is where BYD has a facility in the US That's correct. It will be at that at that facility. You're exactly right. Um and then we will take that chassis to Vegas to one of our one of our neurosites 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 so there is a fair bit of of in house manufacturing that we'll be doing in addition to the the chassis final assembly all in the US. So the the neuron three that's now the sort of the latest iteration, is the will that be

The one that is the the the main consumer facing delivery vehicle or or do you think by that time, by the time you really scale You're gonna be uh on Model four or five or whatever.

No, that'll be it, guy. I hope that's the one that you'll be able to get uh your produce for preparing your meals. I know you're you're a big cook. Um we hope that that's the one that we'll be able to scale across the whole country. Now that is very much a 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 uh 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 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 wanna stay very, very targeted and really nail that application.

W 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,'cause 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 uh human driver might sideswipe 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? I think there are there are a couple 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 uh situation, and then making sure that it pulls over and it stops. Uh, the second is w 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 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 used by

for instance law enforcement for communicating with our mothership and our monitors and and getting any information that they want. And so we we intend to make use of that and and we have you know we've published some of the law enforcement uh interaction plans for how to interact with our vehicle. Um but but we do think that there's uh there's a pretty nice opportunity there to do a really good job of that because we have to do a good job of that anyway, just for our core product. So this is unrelated to the technology, but of course related to the economic environment that we are now presumably entering w neural 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 twelve months. affecting your business, if if at all. Well, we've you know, you we did we did go through layoffs and you know that that that's really a a pretty awful situation. You know, Jay Z and I have have often said that the building the neuro team is what we're most proud of and and here we were having to cut roughly twenty percent of it and yeah and that was all on us.

for growing too aggressively and being too optimistic about the market and funding conditions. And 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're we're a company that is is doing some some pretty crazy things. Uh and we're very excited about it and I think we're making a lot of progress, 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, um, massive business. And so we are trying to be very, very thoughtful about how we manage our bone as a company, uh 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 in 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 we generally feel really, really good about where the company is. Um, 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, uh those that are still with us and those that aren't, 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. Um, and really wanna go and realize it, um, and nail this for for everyone that has ever contributed. Yeah. So ta let's go sort of ten years into the future now, right? And there are obviously competitors to there are other other companies who are working on this kind of technology, but In ten 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. Fo deliveries, is is that what we're talking about, mainly? 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 uh either way at those ninety three 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 uh products for for customers. So One one example is

uh packages. So right now, I mean, most of us get umpteen packages delivered from Amazon, FedEx, and others. 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 it's harder for it to leave it on your doorstep.

you know, we considered slingshots and drones and and other things that could take it from the vehicle to your front door, but but as of yet, that 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, um 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 uh toiletries or emergency goods or you know, 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 we do see an opportunity where you can start batching different services. And and effectively as an in consumer, you're 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 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. That's Dave Ferguson, co-founder of Nuro. Dave, thanks so much.

Thanks guys, been a pleasure. Really appreciate it. 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, and on Instagram, I'm at guy.Roz. If you want to contact the team, our email address is hibt at id.wondery.com. This episode was produced by Chris Massini with editing by John Isabella. Our audio engineer was Andy Hewther. Our music was composed by Ramteen Arablui.

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