Waabi Raises $1B from Uber and VCs

0:00Welcome to the podcast. I'm your host, Jaden Schaefer. Today on the podcast, we're talking about a company called Wabi that has just raised a billion dollars. They partnered with Uber. They're getting into robo taxis. It's an autonomous.

0:30landscape looks like for some of these autonomous trucking and driving companies. Before we get into it, I wanted to mention if you want to build tools without knowing how to code, I'd love for you to go check out AIbox.ai, my own startup, where you can describe any tool or workflow that you do and have it linked together to different AI models, input prompts, and automatically build you a tool that you can use over and over again to help automate your tasks. In addition, you get access to over 40 different AI models if you want to chat with them like ChatGPT, 11Labs, Anthropic, audio image text tons of amazing models it's 20 bucks a month you get access to all of that so you can go check out aibox.ai all right let's talk about what's happening with wabi something that's interesting to me with the wabi story of course you know a billion dollars raised is absolutely incredible a partnership with uber is incredible and i think lots of times you'll see like a partnership happen first and then you go raise the money after but they kind of did these things or at least the way they announced them that happened at the same time i'm sure there was probably talk that helped to raise the money.

1:28But this is essentially a partnership with Uber to deploy self-driving cars on their ride-sharing platform, which is going to make Wabi's first expansion beyond just autonomous trucking. This is what they've kind of been working on. So this is their Series C. It was co-led by Koshla Ventures, G2 Ventures, and then that and a bunch of others kind of put in$750 million. And alongside that, you have Uber that came in with $250 million, so they did a total of$1 billion. I think that Uber backing that$250 million is tied to deploying about 25 ,000 or more of Wabi driver-powered robo-taxis. And what's interesting is this is exclusively on Uber's platform, even though the company didn't share a timeline for, you know, when they're going to have all of this rolled out.

2:16And I think right now, when you're looking at it, it looks like a really big bet that Wabi's first, you know, kind of this AI first approach is possibly going to succeed where a lot of others have struggled in this. This is not an easy thing, scaling a single autonomous driving system across a whole bunch of different vehicle types. And then commercial use, I think adds a whole nother level of complexity to all of this. So there's a bunch of competitors doing this, right? I think everyone knows about Waymo and of course, Tesla. Waymo actually previously attempted to operate both robo taxis and autonomous trucking before they got out of autonomous trucking altogether, They completely left that industry.

2:51So Wabi's founder and CEO is Raquel Ertsson. And she said that her company's capital efficient strategy and generalized AI architecture give it a bit of a structural advantage. This is a direct quote, she said, our core technology enables for the first time a single solution that can operate across multiple verticals at scale. It's not about running two programs or maintaining two stacks. This is really interesting, because I mean, technically a car is a car and driving is driving but if anyone has ever tried to drive a semi truck before you know that i mean this is very different you have to get a different type of license these are massive vehicles the way that it backs up the way that you know everything's happening on that truck is very different than a regular car so you know they're saying look a car is a car these are you know it's using the exact same system but we have seen other players like waymo try to get into both just vehicles and freight and exit the freight because it was kind of maybe too risky or too hard or they felt like they could come to market with the cars sooner and maybe Waymo gets into it but usually when you see a company try something and exit out of it it just feels like that's not the vertical they're going to go after so here it appears that this is something they're actually going to attack which is going to be interesting this whole partnership is also bringing Yuritsu's career full circle the the ceo because before founding wabi she was actually the chief scientist at uber's autonomous vehicle division uber atg which uber actually sold to aurora innovation in 2020 and so she already works with uber freight and now this new agreement i think is going to really make that a lot deeper it's kind of interesting right like she was literally working in uber working on this uber sells off this kind of autonomous vehicle division to another company she works there she starts her own company and uber signs a deal with her and gives her 250 million dollars so i mean obviously this is a problem that uber's been trying to solve for a long time they probably felt like they couldn't do it and then when someone else did they they were willing to give them a big check so wabi is now joining a whole bunch of different companies that are doing this um and also other ones that are deploying on uber's platform so waymo neuro avride wave we ride momenta all of these are getting onto the uber platform and and so they're kind of coming alongside them the deal also is coming at the same time that uber has launched this new internal group called uber av labs which is going to let uber vehicles collect real world data for all of their autonomous partners so all of these companies that are on the platform also are going to get more data to help train their models to make them better and it's kind of interesting because tesla a lot of times kind of talks about how look we have like millions of vehicles on the road and this is what's making our AI, you know, autonomous driving system so good, which is true.

5:37But it's not like other people can't replicate that. Because if you have this whole network over on Uber, now Waymo, Nervo, Avaride, you know, WeRide, Momentum, all of these are also going to be getting data and collecting and sharing and making all of these autonomous riding better as well. So you're going to see kind of everyone else share their data. Tesla seems to be the one that has the most of it and so it's gonna be interesting to see which of these two models win unlike a lot of different av development that is going to rely on a whole bunch of kind of real world data sets a really massive real world data set wabi says that their system is less data hungry and the way they've done this is actually really fascinating to me so the wabi driver is essentially trained and validated inside of what is called wabi world this is a closed loop similar simulation environment that automatically builds digital twins of real environments so it's you know simulating all of the sensors in real time.

6:31It's generating edge case scenarios. It's allowing the system to learn from its mistakes without human intervention. So, you know, they kind of have this whole simulated world they've built and the AI is learning to drive inside of it. But the simulated world is, you know, very similar to the real world, which we can do these types of things when we have, you know, technology like Google Maps and Street View and all this other stuff. And the technology behind it, really, because I don't think Google's licensing that data, but you could go drive a car around and get real information and then use that to replicate these kind of digital worlds that it's used to simulate with.

7:03So according to Year at Sun, this like approach that they're taking is going to make their system and it's going to allow it to reason about its surroundings more like a human driver and generalize from fewer examples than traditional AV systems. Wabi has spent the past four and a half years developing that technology and they've done it for highways and surface street tracking. Something that's really interesting to me is the fact that, you know, with something like Waymo, which I've driven in Waymo's in the past before and phenomenal technology, really cool cars in Phoenix, I would drive around there to get from the airport to my podcast studio all the time.

7:37But the problem with Waymo's, and I know this will get solved at some point, but Waymo's, what I realized when I first did my first Waymo ride was usually it's a 15 minute drive from the airport to my podcast studio, and it was 35 minutes and I was like what the heck why is it taking 35 minutes and it was because it wouldn't go on the freeway it was going on back roads and that's kind of where Waymo was at at the time and maybe these things are changing um but the freeway you know so like we talked about the difference between regular vehicles and semi trucks or you know freight now there's also a difference between back roads and freeway and so it feels like they have to do like Wabi has to do some of the hardest things they have to do freight on freeways like right off the bat these are the two things that they need their company to be able to do because that's how you transport freight across the country is over freeways.

8:22So, I mean, it feels like they have a lot of difficult problems to solve, but it feels like they're solving them. Yuratsu says that Wabi Brain already generalizes across vehicle types. She even hinted that robotics could be the company's next vertical, which is really interesting. From kind of the get-go, they're collecting and simulating passenger vehicle data alongside the trucking work, which I think shows that robo-taxis were kind of always part of the long-term roadmap for them. And that strategy, according to her, has basically allowed Wabi to build a lot faster with a lot less capital than, you know, maybe like some other first-generation AV companies.

9:00She said, we don't need massive fleets, enormous data centers, or endless numbers of people and chips. So, I mean, this could be a unique approach. You saw others fail to accomplish this. And if their approach, you know, is really able to do with less data, less compute, and less money, this could be a massive competitive advantage that they have coming to the market. So with this current billion dollar round, Wabi's total funding is now at about 1.28 billion dollars. They did a 200 million dollars Series B in June of 2024. So if you're just kind of comparing that, Aurora Innovations has raised about 3.4 billion dollars.

9:35Kodiak Robotics has raised about 448 million dollars. These are some other competitive competitors in the landscape. So Wabi has already launched a whole bunch of commercial trucking pilots. They're mostly they're doing this in Texas and they have human drivers in the cab. They've already planned to deploy a full driverless truck on public highways by the end of last year. That was kind of the plan, but their timeline got pushed into somewhere in the next future coming quarters. I think anyone that's been following autonomous driving knows that that kind of deadline push is something that happens we've seen that a lot with tesla over the years and it's essentially because i mean you want to be optimistic but at the same time if the safety rating isn't there if it's not perfect you just can't deploy these systems until it's completely ready so according to them they're also working with volvo to build some purpose-built autonomous trucks which they're which they showed off last october uh air at sue says that software is ready but that the vehicles themselves still need full validation before launch she's really confident that there's going to be a lot of demand for this.

10:39She kind of points to Wabi's direct-to-consumer model that basically allows shippers to purchase autonomous ready trucks outright. And then combining that with Uber's partnership, she thinks that Wabi can scale really quickly with a highly reliable product. She said, quote, we're still in the early innings of robo-taxi deployment. There's a lot more scale to come. She didn't share a lot of details about which automaker they're going to partner with for their Uber robo-taxis, right? Because, you know, it's not like they develop their own car, they usually partner with something, whether that's a Volvo or with another company to build the actual vehicle.

11:12So we don't know what vehicle is actually going to be used for the robo taxis, the Uber robo taxis. She said that the company was planning to follow the same vertically integrated approach it uses in trucking by embedding sensors and autonomy technology directly on the factory floor. So it's not like they buy the vehicles and they retrofit them. They're actually adding all of the sensors, all of the technology on the factory floor with their partner. She said, quote, we believe in fully integrated, redundant platforms built with OEMs. That's how you create technology that is both safe and truly scalable.

11:44There's, you know, a whole bunch of people got in on this round. I was mentioning some at the beginning, but they also had Nventures, Volvo Group, Venture Capital, Porsche Automotive, Holdings, BlackRock, BDC, Capital Thrive Venture Fund. There's a bunch of others. But I think it's interesting. I mean, once you start looking at the car companies that are invested in this and the partners, right? A lot of this money is coming from people that are going to make money from this. You see Uber, you see Volvo, you see Porsche, and it gives you an idea of some of the vehicles and manufacturers that they're going to be working with in the future.

12:15So this is a fascinating area. I'll keep you up to date on everything with autonomous self-driving. If you enjoyed the episode, make sure to leave a rating and review wherever you get your podcasts. It helps to show a ton. I really appreciate them. I hope you all have a wonderful rest of your day and I will catch you in the next episode. Also, make sure to check out AIbox.ai. If you want to save money and cancel a dozen of your AI subscriptions, you get them all on one platform for 20 bucks a month. Link in the description. Okay, I'll see you in the next episode.