The Exchanges

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

A 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, uh, 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. 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.

AI assessment note: “So for that competition, I actually joined Intel.”

Q Wow. So you end up at Carnegie Mellon. I think you're there from 2002 to 2006, and you did your PhD there in robotics 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?

A 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 you know, I got that wrong many times. I originally thought I was going to be a lawyer when I first went to university, uh, and that, that didn't work out. Um, and so I thought that I was going to 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, 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…

AI assessment note: “when I was doing my PhD, I thought that I would be a professor.”

Q I know you did a partnership with Kroger. I think Kroger is the second or maybe the biggest grocery chain in the US. Um, this was presumably a pilot, but how did the pilot work?

A 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 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 fries. 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, uh, 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, ah, the end of, I think that was the end of 2018, early 20 19, ah, that we did that. Um, and, you know, I think ever since we've continued strength, certainly strengthening our relationship with Kroger, ah, with whom we have a big, sor…

AI assessment note: “the idea was that Kroger customers could order delivery from their local Kroger”

Q these vehicles start to come online, right, tell me, help me understand how they operate. I mean, um, we've had, as you know, we've had crews 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, ah, that navigate the vehicles. How How do your vehicles work? How are they able to navigate roads safely?

A 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 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, 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 figure out what's, what's the right move for them to make. Now, one of the differentiators for us, because we're only 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 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, 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 vehic…

AI assessment note: “we have cameras, we have LIDARs, we have radars, we have thermal cameras”

Q Hmm. Alright, so you, you were with Intel for a bit of time, and then did you stay in Pittsburgh? What'd you do after that?

A After the Urban Challenge, I, 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, ah, 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, um, using machine learning, which, you know, was, it was really exciting. I think it's a, it's, it's a fun playground, uh, the world of finance 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 ha…

AI assessment note: “I spent a few years out in New York and I worked for a hedge fund”

Q 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 gonna be different about what you guys wanted to pursue rather than what you already were doing at, at Google at that point?

A 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 Transformation and how we interact in the physical world. And, and 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. Um, 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 were going to work on, and so the two of us spent a …

AI assessment note: “we settled on transforming local commerce through self-driving delivery”

Q 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, if at all?

A Well, we've, you know, we did, we did go through layoffs, and you know, 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 20% of it, and, 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 are a company that is, is doing some, some pretty crazy things. Uh, 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 as a massive, um, massive business. And so, We are trying to be very, very thoughtful about how we manage our burn 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 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, …

AI assessment note: “We are trying to be very, very thoughtful about how we manage our burn”