1 00:00:02,480 --> 00:00:07,280 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. 2 00:00:07,840 --> 00:00:10,760 Speaker 2: You've just raised sixteen billion dollars. It's a lot of money. 3 00:00:11,480 --> 00:00:14,360 Speaker 2: What is it unlocked for way Mo over the next 4 00:00:14,400 --> 00:00:16,000 Speaker 2: twelve twenty four months. 5 00:00:16,480 --> 00:00:19,360 Speaker 3: Raising the sixteen billion dollars and at one hundred and 6 00:00:19,400 --> 00:00:22,759 Speaker 3: twenty six billion dollar valuation is really a vote of confidence. 7 00:00:23,360 --> 00:00:25,520 Speaker 3: I mean, this team has been heads down for a 8 00:00:25,680 --> 00:00:30,080 Speaker 3: long time trying to bring this sort of scientific project 9 00:00:30,600 --> 00:00:33,919 Speaker 3: into reality and app scale. And so it's a huge 10 00:00:33,960 --> 00:00:37,640 Speaker 3: event of confidence not only from our majority investor, Alphabet, 11 00:00:37,880 --> 00:00:41,280 Speaker 3: but also from our co lead investors Sequoia and DST 12 00:00:41,920 --> 00:00:45,640 Speaker 3: and Dragoneer, as well as a host of world class 13 00:00:45,680 --> 00:00:49,199 Speaker 3: existing and new investors. And it just allows us to 14 00:00:49,240 --> 00:00:52,560 Speaker 3: continue to scale our business. Right now, we're laying the 15 00:00:52,600 --> 00:00:56,200 Speaker 3: groundwork for over twenty cities in this year alone. 16 00:00:57,120 --> 00:00:59,520 Speaker 2: I should point out, you know, we reported Alphabet will 17 00:00:59,560 --> 00:01:02,120 Speaker 2: account for the vast majority of that sixteen billion. But 18 00:01:02,160 --> 00:01:07,800 Speaker 2: it is interesting, so Quoia Capital, DST, Dragonnaire beyond you investors, 19 00:01:08,319 --> 00:01:11,039 Speaker 2: what do we interpret from that that they came in 20 00:01:11,319 --> 00:01:13,160 Speaker 2: at this stage of the company's life. 21 00:01:13,760 --> 00:01:16,080 Speaker 3: I think it's important to interpret that this is an 22 00:01:16,120 --> 00:01:20,520 Speaker 3: inflection point, right like in twenty twenty five, we quadrupled 23 00:01:20,600 --> 00:01:23,360 Speaker 3: the number of trips that we are providing, So we 24 00:01:23,440 --> 00:01:28,200 Speaker 3: offered fifteen million rides and we have over twenty million 25 00:01:28,240 --> 00:01:31,040 Speaker 3: lifetime rides. So it was just a really important year. 26 00:01:31,480 --> 00:01:34,200 Speaker 3: And now that we've launched Miami, that's across six cities, 27 00:01:34,560 --> 00:01:37,039 Speaker 3: but at that time it was across five cities, and 28 00:01:37,120 --> 00:01:40,440 Speaker 3: so demonstrating not only that the technology works that were 29 00:01:40,480 --> 00:01:43,160 Speaker 3: able to drive the safety impacts that we've been focused on, 30 00:01:43,640 --> 00:01:46,080 Speaker 3: you know, with when we were at one hundred and 31 00:01:46,080 --> 00:01:49,560 Speaker 3: twenty seven million miles, we were able to demonstrate a 32 00:01:49,720 --> 00:01:54,640 Speaker 3: ninety percent that we had ninety percent fewer serious injury 33 00:01:54,680 --> 00:01:58,480 Speaker 3: causing crashes or worse. That's the kind of safety output 34 00:01:58,560 --> 00:02:01,000 Speaker 3: that drives us. That's our mission to be the world's 35 00:02:01,000 --> 00:02:04,440 Speaker 3: most trusted driver. So coming in at this point demonstrates 36 00:02:04,440 --> 00:02:08,360 Speaker 3: that consumers are adopting it, the safety case is being made, 37 00:02:08,560 --> 00:02:10,960 Speaker 3: and it's just really exciting time to join the team. 38 00:02:11,080 --> 00:02:14,480 Speaker 2: You set the same for expansion across twenty cities this year. 39 00:02:14,560 --> 00:02:18,240 Speaker 2: Right right now, you're doing four hundred thousand paid rides 40 00:02:18,280 --> 00:02:22,040 Speaker 2: a week across six cities. It's a greater scale than 41 00:02:22,080 --> 00:02:24,600 Speaker 2: when you and I talked to more than a year ago, 42 00:02:24,840 --> 00:02:27,280 Speaker 2: which seemed to be to be a time of pace. 43 00:02:27,400 --> 00:02:31,360 Speaker 2: Then what's the biggest challenge of operating a robotaxi service 44 00:02:32,120 --> 00:02:34,000 Speaker 2: at that new scale that you're developing. 45 00:02:34,639 --> 00:02:37,919 Speaker 3: I think everything is really exciting right now, and there 46 00:02:37,960 --> 00:02:40,960 Speaker 3: are many many things to be learned as we go. 47 00:02:41,440 --> 00:02:44,359 Speaker 3: Right like some markets are still not open and they're 48 00:02:44,440 --> 00:02:48,240 Speaker 3: really important transportation hubs around the world, like New York City, 49 00:02:48,720 --> 00:02:50,960 Speaker 3: you know, and so we were the first company to 50 00:02:51,000 --> 00:02:55,000 Speaker 3: receive a testing permit where we had driver supervision of 51 00:02:55,120 --> 00:02:57,240 Speaker 3: fully autonomous testing in the city. 52 00:02:58,120 --> 00:02:59,639 Speaker 4: And we believe now. 53 00:02:59,360 --> 00:03:01,960 Speaker 3: With Governor goal that we will be able to be 54 00:03:02,040 --> 00:03:04,760 Speaker 3: the first company to launch a New York City, a 55 00:03:04,800 --> 00:03:07,000 Speaker 3: New York State. But you know, this is going to 56 00:03:07,000 --> 00:03:10,040 Speaker 3: be a path actually figuring out the regulatory landscape. 57 00:03:10,000 --> 00:03:12,680 Speaker 2: There is something there isn't there. City versus states, state 58 00:03:12,760 --> 00:03:15,280 Speaker 2: versus ver. We will talk about it. Yeah, I got 59 00:03:15,320 --> 00:03:17,160 Speaker 2: a lot of interest when I said that I was 60 00:03:17,160 --> 00:03:19,919 Speaker 2: going to be speaking with you about sixteen billion dollars 61 00:03:19,960 --> 00:03:22,320 Speaker 2: A lot of money, but actually how will you use it? 62 00:03:22,400 --> 00:03:26,720 Speaker 2: There's a tension between scaling operations the fleet. You know, 63 00:03:26,760 --> 00:03:29,480 Speaker 2: you've got to have more cars, but also a commitment 64 00:03:29,520 --> 00:03:32,160 Speaker 2: to invest in technology, and I wanted to teach you 65 00:03:32,240 --> 00:03:34,800 Speaker 2: how far you've thought about how much goes into each 66 00:03:34,840 --> 00:03:35,880 Speaker 2: of those buckets. 67 00:03:36,280 --> 00:03:38,960 Speaker 3: Yeah, so, first and foremost, when we think about twenty 68 00:03:39,000 --> 00:03:43,400 Speaker 3: twenty six, just the year ahead of us, execution execution execution, 69 00:03:43,600 --> 00:03:47,040 Speaker 3: So scaling across these twenty cities that were laying the 70 00:03:47,040 --> 00:03:50,600 Speaker 3: groundwork for continuing to grow our world class team is 71 00:03:50,600 --> 00:03:52,240 Speaker 3: obviously super important to us. 72 00:03:53,320 --> 00:03:55,760 Speaker 4: Making sure that we are continuing. 73 00:03:55,160 --> 00:03:58,320 Speaker 3: To cost down our hardware stack and prove out our 74 00:03:58,400 --> 00:04:02,040 Speaker 3: unit economics while scaling our fleet. And so we have 75 00:04:02,240 --> 00:04:06,800 Speaker 3: our fully electric ipace fleet. We are starting to introduce 76 00:04:06,840 --> 00:04:10,080 Speaker 3: the OHI vehicles and then you will see the Ionic 77 00:04:10,120 --> 00:04:12,480 Speaker 3: fives come online, and so making sure that we are 78 00:04:12,520 --> 00:04:16,000 Speaker 3: investing for the long term for a sustainable business is 79 00:04:16,040 --> 00:04:16,640 Speaker 3: what we're really. 80 00:04:16,560 --> 00:04:18,640 Speaker 1: Fused to see the OHI vehicles testing. 81 00:04:19,320 --> 00:04:22,320 Speaker 2: If I am a user of the service right now, 82 00:04:22,360 --> 00:04:24,800 Speaker 2: will I soon be able to actually get into an. 83 00:04:24,680 --> 00:04:27,800 Speaker 3: Ohai you will this year be able to Right now, 84 00:04:27,880 --> 00:04:30,200 Speaker 3: we've only throughout twenty twenty five. In the beginning of 85 00:04:30,200 --> 00:04:33,040 Speaker 3: this year, had employees in three cities. 86 00:04:33,360 --> 00:04:36,040 Speaker 2: We just had a huge weekend here in the Bay Area, 87 00:04:36,240 --> 00:04:37,880 Speaker 2: San Francisco, but Santa. 88 00:04:37,600 --> 00:04:38,719 Speaker 1: Clara super Bowl. 89 00:04:38,880 --> 00:04:42,799 Speaker 2: Yes, I across social media saw a lot of people 90 00:04:42,920 --> 00:04:47,560 Speaker 2: reflect on their first experience in a robotaxi, some of 91 00:04:47,600 --> 00:04:52,240 Speaker 2: them of course with Waimo, was that a tangible, meaningful 92 00:04:52,279 --> 00:04:54,720 Speaker 2: moment for the company recently is the town? 93 00:04:55,000 --> 00:04:55,320 Speaker 4: Yes? 94 00:04:55,800 --> 00:04:57,839 Speaker 1: What data? What evidence can we can we point to 95 00:04:57,880 --> 00:04:59,040 Speaker 1: on how big a weekend? 96 00:04:59,279 --> 00:05:03,960 Speaker 3: Yeah Bowl is a reminder for us that Weymo is 97 00:05:04,000 --> 00:05:06,640 Speaker 3: part of the fabric of the Bay Area, right like 98 00:05:06,760 --> 00:05:10,320 Speaker 3: people were able to hail rides from SFO from San 99 00:05:10,400 --> 00:05:13,400 Speaker 3: Jose Airport, people were able to get to and from 100 00:05:13,440 --> 00:05:14,640 Speaker 3: the Levi Stadium. 101 00:05:15,040 --> 00:05:15,240 Speaker 4: You know. 102 00:05:15,279 --> 00:05:18,520 Speaker 3: We obviously did a lot of fun activations with influencers, 103 00:05:19,279 --> 00:05:22,120 Speaker 3: but it's just a reminder that people are using the 104 00:05:22,160 --> 00:05:27,720 Speaker 3: Waimo service in every day errands, doctor's appointments, you know, 105 00:05:27,760 --> 00:05:32,279 Speaker 3: getting kids to practice, in big life moments, weddings, picking 106 00:05:32,400 --> 00:05:36,480 Speaker 3: up a child from daycare, having a baby, you know, 107 00:05:36,520 --> 00:05:39,720 Speaker 3: going to their going to the hospital, pregnant, coming home 108 00:05:39,800 --> 00:05:43,000 Speaker 3: from the hospital with a newborn, and then these large 109 00:05:43,040 --> 00:05:46,039 Speaker 3: cultural moments, and so we've had a number of them. Obviously, 110 00:05:46,160 --> 00:05:48,640 Speaker 3: we started the month with the Grammys. We had a 111 00:05:48,640 --> 00:05:52,240 Speaker 3: host of activations there, then the Super Bowl, and then 112 00:05:52,279 --> 00:05:55,320 Speaker 3: of course we have the All Star weekend coming in 113 00:05:55,360 --> 00:05:59,120 Speaker 3: Los Angeles, and so we're just finding this intersection of 114 00:05:59,160 --> 00:06:02,280 Speaker 3: everyday life and then real enthusiasm because a lot of 115 00:06:02,320 --> 00:06:04,200 Speaker 3: people came to the Bay Area for the Super Bowl 116 00:06:04,560 --> 00:06:07,040 Speaker 3: and we're not in their city, and it's the thing 117 00:06:07,080 --> 00:06:08,919 Speaker 3: they had heard from their friends in the area. You 118 00:06:08,960 --> 00:06:11,960 Speaker 3: have to check out Weimo, And so we saw so 119 00:06:12,040 --> 00:06:15,400 Speaker 3: many downloads and so many happy writers while they were here. 120 00:06:16,040 --> 00:06:20,000 Speaker 2: Weimo's reputation is growing globally and we're going to talk 121 00:06:20,040 --> 00:06:23,440 Speaker 2: about about the literal expansion of your operations. But with 122 00:06:23,520 --> 00:06:26,880 Speaker 2: this funding round, you know, it's a who's who of 123 00:06:26,960 --> 00:06:30,960 Speaker 2: investors now on the cap table. It's a big raise 124 00:06:31,040 --> 00:06:34,120 Speaker 2: at a premium valuation. How much of that is sort 125 00:06:34,160 --> 00:06:37,320 Speaker 2: of setting the pieces in motion to life eventually as 126 00:06:37,320 --> 00:06:40,560 Speaker 2: a public company. Is that something that you and Dmitri 127 00:06:40,720 --> 00:06:43,680 Speaker 2: and the rest of the leadership plan for or is 128 00:06:43,720 --> 00:06:46,000 Speaker 2: their merit staying as you are now? 129 00:06:46,760 --> 00:06:49,960 Speaker 3: You know, we are just laser focused on execution, you know, 130 00:06:50,160 --> 00:06:54,800 Speaker 3: building Weimo to be financially responsible, operationally excellent, and then 131 00:06:54,839 --> 00:06:58,000 Speaker 3: make sure we maintain the safety culture. Like that's what 132 00:06:58,040 --> 00:07:01,159 Speaker 3: we're really focused on. Having this voe of confidence, as 133 00:07:01,200 --> 00:07:04,000 Speaker 3: you said, not only from alphabet, but from our three 134 00:07:04,279 --> 00:07:07,480 Speaker 3: colleagues from this round, and from all of the new 135 00:07:07,480 --> 00:07:10,200 Speaker 3: investors who decided to join our cap table and the 136 00:07:10,280 --> 00:07:13,160 Speaker 3: existing ones who doubled down on their belief that this 137 00:07:13,320 --> 00:07:16,280 Speaker 3: is the right opportunity to fund. And so we just 138 00:07:16,320 --> 00:07:20,280 Speaker 3: feel humbled. But also there's a lot to do. So 139 00:07:20,320 --> 00:07:22,760 Speaker 3: we're just really focused on making sure that we can scale, 140 00:07:23,240 --> 00:07:26,600 Speaker 3: focusing on our two first international launches, you know, London 141 00:07:26,640 --> 00:07:29,960 Speaker 3: and Tokyo, and scaling across the United States. 142 00:07:30,520 --> 00:07:31,640 Speaker 1: Let's talk about the growth. 143 00:07:32,160 --> 00:07:34,840 Speaker 2: A lot of people just want to understand in some 144 00:07:34,920 --> 00:07:37,160 Speaker 2: of those cities where people are frustrated because the service 145 00:07:37,200 --> 00:07:39,560 Speaker 2: doesn't exist, what does it take to launch in a 146 00:07:39,600 --> 00:07:43,400 Speaker 2: city to go from mapping that city through to a 147 00:07:43,480 --> 00:07:45,920 Speaker 2: full paid commercial service. 148 00:07:46,360 --> 00:07:50,560 Speaker 3: Now, if the regulatory climate of a city is welcoming, 149 00:07:51,280 --> 00:07:55,200 Speaker 3: then if then we can show up and map and 150 00:07:55,280 --> 00:07:57,520 Speaker 3: launch in a couple of months, like we did in Miami. 151 00:07:58,080 --> 00:08:00,600 Speaker 3: You know, that's a city where you know, they were 152 00:08:00,600 --> 00:08:03,160 Speaker 3: welcoming and they were ready, and we were ready, and 153 00:08:03,200 --> 00:08:04,960 Speaker 3: so we showed up. You know, we have a fleet 154 00:08:04,960 --> 00:08:07,840 Speaker 3: operating partner, and we were able to launch quite quickly 155 00:08:07,920 --> 00:08:11,640 Speaker 3: after we first arrived. I think in a lot of cities, 156 00:08:11,760 --> 00:08:16,120 Speaker 3: especially cities that are meaningful from a transportation perspective, where 157 00:08:16,160 --> 00:08:20,440 Speaker 3: we're helping, we're working engaging with policymakers. You know, we 158 00:08:20,640 --> 00:08:25,320 Speaker 3: have the burden to demonstrate our safety impact. And so 159 00:08:25,560 --> 00:08:28,120 Speaker 3: with the one hundred and twenty seven million miles in 160 00:08:28,720 --> 00:08:32,880 Speaker 3: ninety percent fewer injury, serious injury causing crashes or worse, 161 00:08:33,280 --> 00:08:35,360 Speaker 3: you know, we have to educate them on that kind 162 00:08:35,360 --> 00:08:39,520 Speaker 3: of impact. Eighty two percent fewer airbag deployments. You know, 163 00:08:39,760 --> 00:08:44,360 Speaker 3: this isn't something that any fleet based business has been 164 00:08:44,400 --> 00:08:47,560 Speaker 3: able to come in and give policy makers data. So 165 00:08:47,679 --> 00:08:50,640 Speaker 3: assuming that we can do that and then grow trust, 166 00:08:51,080 --> 00:08:54,120 Speaker 3: and you know, we do that by partnering with organizations 167 00:08:54,120 --> 00:08:57,720 Speaker 3: in markets who have been trying to solve road safety issues. 168 00:08:57,960 --> 00:09:02,160 Speaker 3: They've been trying to expand mobility options for residents, and 169 00:09:02,240 --> 00:09:04,640 Speaker 3: so we partner with them. And then obviously we work 170 00:09:04,679 --> 00:09:07,760 Speaker 3: with law enforcement and first responders to train them on 171 00:09:07,800 --> 00:09:09,080 Speaker 3: horror technology works. 172 00:09:10,120 --> 00:09:12,800 Speaker 2: We do not yet have, although there has been progress 173 00:09:12,840 --> 00:09:17,520 Speaker 2: towards just this week, a federal level framework set of rules. 174 00:09:19,080 --> 00:09:22,440 Speaker 2: What do you think the direction of travel is with that? 175 00:09:22,720 --> 00:09:25,240 Speaker 2: And you know, clearly if you had to deal with 176 00:09:25,240 --> 00:09:27,080 Speaker 2: one set of rules and not a city by city, 177 00:09:27,160 --> 00:09:31,160 Speaker 2: let alone state by state basis or case, you'd be 178 00:09:31,240 --> 00:09:33,440 Speaker 2: making a bit more progress, I suppose. 179 00:09:33,880 --> 00:09:36,320 Speaker 3: Yeah, we think it's really important that there is a 180 00:09:36,360 --> 00:09:41,160 Speaker 3: federal av standard. We've been advocating for sort of a 181 00:09:41,200 --> 00:09:45,400 Speaker 3: safety case based approach because the technologies are different, and 182 00:09:45,440 --> 00:09:47,640 Speaker 3: we think that the burdens should be on companies to 183 00:09:47,720 --> 00:09:50,840 Speaker 3: demonstrate why you believe your technology is safe enough. We 184 00:09:50,880 --> 00:09:54,160 Speaker 3: also think there should be transparency requirements. You know, people 185 00:09:54,160 --> 00:09:57,000 Speaker 3: should have to demonstrate how many trips are you providing? 186 00:09:57,200 --> 00:10:00,360 Speaker 4: You know, I don't right now, the balance isn't quite there. 187 00:10:00,400 --> 00:10:03,240 Speaker 3: I mean some states require a lot of reporting, some 188 00:10:03,320 --> 00:10:06,480 Speaker 3: don't require as much reporting. I think the United States 189 00:10:06,520 --> 00:10:10,120 Speaker 3: has an opportunity with this technology to lead globally, and 190 00:10:10,120 --> 00:10:12,679 Speaker 3: I don't think you can lead globally if it's a 191 00:10:12,720 --> 00:10:16,880 Speaker 3: framework that's governed by multiple jurisdictions across the states. And 192 00:10:16,960 --> 00:10:19,600 Speaker 3: it's a way to slow down the adoption of this 193 00:10:19,679 --> 00:10:22,840 Speaker 3: technology not only in the US, but in other markets. 194 00:10:23,720 --> 00:10:27,360 Speaker 2: New York City, New York City, not necessarily New York State. 195 00:10:27,880 --> 00:10:28,880 Speaker 1: A lot of people. 196 00:10:28,600 --> 00:10:32,559 Speaker 2: Want to know what's the roadblock there upon the expression 197 00:10:33,400 --> 00:10:37,240 Speaker 2: and what's the timeline? You know, you work closely with 198 00:10:37,360 --> 00:10:41,160 Speaker 2: the authorities. But that is a big potential market. 199 00:10:41,600 --> 00:10:43,720 Speaker 3: Yeah, that's a market where you know, we're just going 200 00:10:43,800 --> 00:10:47,120 Speaker 3: to have to do the work and demonstrate our safety 201 00:10:47,160 --> 00:10:50,800 Speaker 3: outcomes and earn the trust and shizzle away at it 202 00:10:50,880 --> 00:10:51,320 Speaker 3: over time. 203 00:10:51,360 --> 00:10:53,120 Speaker 1: Do they have the rules for you to follow. 204 00:10:53,520 --> 00:10:57,199 Speaker 3: They do not have rules that allow the human operator 205 00:10:57,280 --> 00:10:59,480 Speaker 3: to be removed from the vehicle entirely. 206 00:10:59,240 --> 00:11:01,720 Speaker 2: And until that changed, and until that changes. 207 00:11:01,840 --> 00:11:04,440 Speaker 3: But you know, there is an interest in doing this 208 00:11:04,600 --> 00:11:06,960 Speaker 3: in the state, even outside of the city, and that 209 00:11:07,000 --> 00:11:10,400 Speaker 3: gives us an opportunity to grow more fans, and fans 210 00:11:10,520 --> 00:11:13,960 Speaker 3: actually are calling for this in cities where our technology 211 00:11:14,000 --> 00:11:17,720 Speaker 3: can't be deployed. We are seeing organic campaigns spring up 212 00:11:18,000 --> 00:11:20,760 Speaker 3: saying I want WEIMO in my town, you know. And 213 00:11:21,080 --> 00:11:24,959 Speaker 3: sometimes it's you know, parents of children who will never 214 00:11:25,000 --> 00:11:29,800 Speaker 3: have driver's license saying like, Okay, this is a safer alternative. 215 00:11:30,280 --> 00:11:33,080 Speaker 3: Let's bring it in and let's give these children independents. 216 00:11:33,120 --> 00:11:35,520 Speaker 3: And so it's been really exciting for us to see 217 00:11:35,640 --> 00:11:38,400 Speaker 3: people demanding it, and over time that's going to grow. 218 00:11:38,600 --> 00:11:41,000 Speaker 2: Of those twenty cities that are coming this year, New 219 00:11:41,080 --> 00:11:43,520 Speaker 2: York City is not one of them. Fasted in No, 220 00:11:43,679 --> 00:11:47,920 Speaker 2: that's right, San Francisco. The Bay Area is my home. 221 00:11:48,679 --> 00:11:51,440 Speaker 2: London's where I grew up, and I was studying the 222 00:11:51,480 --> 00:11:55,400 Speaker 2: map of the burros that you propose to launch in 223 00:11:56,320 --> 00:11:58,240 Speaker 2: and you correct me if my math is wrong, But 224 00:11:58,440 --> 00:12:01,680 Speaker 2: just based on those burros at launch, this seems to 225 00:12:01,679 --> 00:12:05,880 Speaker 2: be the biggest citywide deployment from the start that you 226 00:12:05,920 --> 00:12:06,760 Speaker 2: guys will have done. 227 00:12:07,280 --> 00:12:10,240 Speaker 1: Is that correct? It? 228 00:12:10,440 --> 00:12:11,640 Speaker 4: Possibly, it's correct. 229 00:12:11,679 --> 00:12:14,200 Speaker 3: I mean, we're in the phases of figuring out the 230 00:12:14,240 --> 00:12:17,960 Speaker 3: specifics around the launch and figuring out the actual framework 231 00:12:18,000 --> 00:12:20,040 Speaker 3: around the launch, and so I don't want to speak 232 00:12:20,080 --> 00:12:22,400 Speaker 3: to you definitively about what we're going to do. But 233 00:12:22,640 --> 00:12:26,720 Speaker 3: what you're speaking to is we're not gated by the technology, right, 234 00:12:26,840 --> 00:12:29,440 Speaker 3: and we have the appetite to scale, and we want 235 00:12:29,440 --> 00:12:31,920 Speaker 3: to partner and do so safely, and we want to 236 00:12:31,920 --> 00:12:34,520 Speaker 3: earn trust. So that's like there's a lot of levers 237 00:12:34,520 --> 00:12:37,040 Speaker 3: there that we have to figure out how to strike 238 00:12:37,080 --> 00:12:38,960 Speaker 3: the right balance and how to make sure that we're 239 00:12:38,960 --> 00:12:41,880 Speaker 3: introducing it to the community both to meet the demand 240 00:12:41,920 --> 00:12:42,360 Speaker 3: and grow. 241 00:12:42,600 --> 00:12:44,840 Speaker 2: I asked, because of those twenty cities to come, London 242 00:12:44,920 --> 00:12:48,120 Speaker 2: is one, yes, and London is now outside of the 243 00:12:48,160 --> 00:12:50,440 Speaker 2: European Union, but it's you know, it's kind of your 244 00:12:50,480 --> 00:12:51,240 Speaker 2: europe launch. 245 00:12:51,400 --> 00:12:53,480 Speaker 1: Yes, what was that experience like? 246 00:12:53,640 --> 00:12:58,319 Speaker 2: Within London's regulatory framework and the UK's regulatory framework. 247 00:12:58,000 --> 00:13:02,480 Speaker 3: They've been extremely forward leaning and interested in seeing how 248 00:13:02,480 --> 00:13:06,200 Speaker 3: this technology could actually improve safety on their roadways. And 249 00:13:06,240 --> 00:13:08,160 Speaker 3: that's where I think, you know, we find a sweet 250 00:13:08,160 --> 00:13:13,120 Speaker 3: spot when people are less sort of complacent about the 251 00:13:13,160 --> 00:13:15,880 Speaker 3: status quo. And I think there's a lot of complacency 252 00:13:16,040 --> 00:13:18,880 Speaker 3: about road debts forty thousand or one point two million globally, 253 00:13:20,040 --> 00:13:22,720 Speaker 3: and when there isn't, I think people are actively interested 254 00:13:22,760 --> 00:13:26,400 Speaker 3: in solutions and then they want to figure out, of course, 255 00:13:26,840 --> 00:13:28,560 Speaker 3: what are the things they need to think. 256 00:13:28,360 --> 00:13:31,280 Speaker 2: Through and learn well, pricing for one, like London has 257 00:13:31,280 --> 00:13:34,680 Speaker 2: take the Bus, Yes, London has take the Tube. London 258 00:13:34,760 --> 00:13:38,600 Speaker 2: is prepared to sort of pay for a robot taxi 259 00:13:38,640 --> 00:13:41,960 Speaker 2: service that's equivalent to a human driven cab Black Cab 260 00:13:41,960 --> 00:13:43,920 Speaker 2: in London or Uber and Lyft. 261 00:13:44,400 --> 00:13:48,640 Speaker 3: Yes, I yes, people are there's you know, obviously, before 262 00:13:48,640 --> 00:13:51,320 Speaker 3: we go in we do a lot of polling, We 263 00:13:51,400 --> 00:13:54,120 Speaker 3: meet with a lot of residents as well as advocates, 264 00:13:54,640 --> 00:13:59,880 Speaker 3: and people are people want safe private spaces. It adds 265 00:14:00,080 --> 00:14:02,840 Speaker 3: to their day versus becoming time that they lose in 266 00:14:02,880 --> 00:14:05,040 Speaker 3: the day, and so it's a you know, the thing 267 00:14:05,080 --> 00:14:09,200 Speaker 3: that's been most exciting is once we introduce the way 268 00:14:09,200 --> 00:14:13,760 Speaker 3: most service into a citiescape, people discover things they didn't 269 00:14:13,800 --> 00:14:16,680 Speaker 3: think they could have, like that hour a day in 270 00:14:16,679 --> 00:14:19,720 Speaker 3: the morning and buy yourself to get something done. 271 00:14:19,840 --> 00:14:21,240 Speaker 4: People have just sacrificed it. 272 00:14:21,400 --> 00:14:24,280 Speaker 3: Yes, and whether that's on transit or whether that's it 273 00:14:24,280 --> 00:14:26,680 Speaker 3: doesn't matter and we're not you know, people want to 274 00:14:26,680 --> 00:14:28,840 Speaker 3: take transit. That's great because you can also sit there, 275 00:14:29,160 --> 00:14:31,520 Speaker 3: just can't sit there maybe until your call on quiet. 276 00:14:31,720 --> 00:14:34,160 Speaker 3: And so this is something that we're hearing from writers 277 00:14:34,200 --> 00:14:36,120 Speaker 3: all the time. I didn't know that I needed this 278 00:14:36,200 --> 00:14:37,000 Speaker 3: the way that I needed that. 279 00:14:37,320 --> 00:14:41,840 Speaker 2: Asia Pacific is also somewhere that is it varies by country, 280 00:14:41,880 --> 00:14:45,080 Speaker 2: but that robotaxis are embraced. You are looking very closely 281 00:14:45,120 --> 00:14:49,400 Speaker 2: at Japan. Yes, what do you see in the Japanese market. 282 00:14:49,400 --> 00:14:52,160 Speaker 2: Of course, you're very closely aligned with Toyota as a 283 00:14:52,160 --> 00:14:56,320 Speaker 2: partner almost a national champion for them in the automotive space. 284 00:14:57,600 --> 00:15:00,920 Speaker 2: Does your hope of launching their go beyond Toyota? Is 285 00:15:00,920 --> 00:15:04,000 Speaker 2: it enabled by Toyota? And again, we have a lot 286 00:15:04,040 --> 00:15:07,080 Speaker 2: of viewers in that country who just want to know when. 287 00:15:07,280 --> 00:15:11,520 Speaker 3: Yes, Yes, when we first thought about Tokyo, Japan, we 288 00:15:11,560 --> 00:15:14,440 Speaker 3: thought about Tokyo, right And when we first thought about Tokyo, 289 00:15:14,640 --> 00:15:17,920 Speaker 3: we decided to partner with Neon Kotsu and Go. And 290 00:15:17,960 --> 00:15:21,600 Speaker 3: that's because that, you know, the cab are such an 291 00:15:21,640 --> 00:15:25,359 Speaker 3: integral part of life there culturally as well culturally exactly. 292 00:15:25,920 --> 00:15:28,080 Speaker 3: And so what that's allowed us to do is we 293 00:15:28,120 --> 00:15:30,920 Speaker 3: have a fleet of vehicles there and the drivers of 294 00:15:30,920 --> 00:15:33,600 Speaker 3: those vehicles are part of that partnership. You know, they're 295 00:15:33,600 --> 00:15:36,840 Speaker 3: collecting the data for us, and so they're like helping 296 00:15:36,880 --> 00:15:39,840 Speaker 3: to usher in this change. There will still be cabs 297 00:15:39,840 --> 00:15:42,720 Speaker 3: for a long time, and there will be an introduction 298 00:15:42,800 --> 00:15:46,440 Speaker 3: of autonomous vehicles, and so finding partners, like you said, 299 00:15:46,560 --> 00:15:49,560 Speaker 3: national champions who can help us navigate not only the 300 00:15:49,600 --> 00:15:53,160 Speaker 3: regulatory climate, but who already have that trust of riders 301 00:15:53,160 --> 00:15:56,440 Speaker 3: and who can help us educate riders that this isn't 302 00:15:56,480 --> 00:15:59,680 Speaker 3: like something they are not welcoming. It's actually something they're 303 00:15:59,720 --> 00:16:03,080 Speaker 3: quite excited about seeing Tokyo become a city of the future. 304 00:16:03,080 --> 00:16:05,800 Speaker 2: From a transport that is a market where the rules 305 00:16:05,840 --> 00:16:09,040 Speaker 2: exist for you to through partners or otherwise, but to 306 00:16:09,680 --> 00:16:12,360 Speaker 2: charge a fair and have a real business, even if 307 00:16:12,400 --> 00:16:13,200 Speaker 2: modest at first. 308 00:16:13,320 --> 00:16:16,080 Speaker 3: That's exactly right, and of course it's something we've helped shape. 309 00:16:16,320 --> 00:16:16,520 Speaker 1: Right. 310 00:16:16,760 --> 00:16:22,480 Speaker 3: You know, there's most places contemplated drivers around the world, right, 311 00:16:22,520 --> 00:16:24,840 Speaker 3: I mean that's the way laws, whether. 312 00:16:24,680 --> 00:16:26,480 Speaker 4: It's fifty years ago or one hundred years ago. 313 00:16:26,480 --> 00:16:29,640 Speaker 3: I mean, they were sort of written to regulate automobiles, 314 00:16:29,720 --> 00:16:32,960 Speaker 3: and automobiles were presumed to be driven by people. And 315 00:16:33,040 --> 00:16:37,160 Speaker 3: so most places we have to think through what needs 316 00:16:37,200 --> 00:16:39,280 Speaker 3: to change in the laws, and then if people are 317 00:16:39,320 --> 00:16:41,400 Speaker 3: willing to work with us on that, then we work 318 00:16:41,440 --> 00:16:42,200 Speaker 3: with them to change it. 319 00:16:42,240 --> 00:16:43,840 Speaker 4: And so in Japan we have a path forward. 320 00:16:44,240 --> 00:16:48,280 Speaker 2: Around the world, the sort of robotaxi race is framed 321 00:16:48,360 --> 00:16:52,240 Speaker 2: in US companies against Chinese technology companies, right. I think 322 00:16:52,240 --> 00:16:54,360 Speaker 2: this is something that Weymo and some of Weimo's executives 323 00:16:54,400 --> 00:16:57,840 Speaker 2: have been kind of candid about this past week in testimony. 324 00:16:59,000 --> 00:17:01,880 Speaker 2: How do you see that that playing out you? For example, 325 00:17:01,880 --> 00:17:05,560 Speaker 2: with Toyota, you have a partner who also in common 326 00:17:05,680 --> 00:17:09,560 Speaker 2: work with Ponyai as an example. It's something you must 327 00:17:09,600 --> 00:17:12,240 Speaker 2: be conscious of in markets where you want to expand 328 00:17:12,320 --> 00:17:13,879 Speaker 2: outside of America in particular. 329 00:17:14,400 --> 00:17:19,160 Speaker 3: Yes, in general, if there are other companies focused on 330 00:17:19,520 --> 00:17:23,680 Speaker 3: autonomous driving to make roads safer. We think that's positive, 331 00:17:24,040 --> 00:17:25,440 Speaker 3: like that is a positive thing. 332 00:17:25,680 --> 00:17:26,320 Speaker 4: We should have. 333 00:17:26,320 --> 00:17:29,960 Speaker 3: Competition around saving lives, and so that's a good thing. 334 00:17:30,400 --> 00:17:32,680 Speaker 3: I think what we don't spend a lot of time 335 00:17:32,720 --> 00:17:36,239 Speaker 3: thinking about is how everyone is thinking about how to 336 00:17:36,240 --> 00:17:39,960 Speaker 3: pursue partnerships. Right now, we're just laser focused on our strategy. 337 00:17:40,200 --> 00:17:42,679 Speaker 3: We're the only company that is offering a twenty four 338 00:17:42,840 --> 00:17:47,040 Speaker 3: x seven service across six markets in the US, with 339 00:17:47,160 --> 00:17:51,120 Speaker 3: ambitions to be in many more this year and launch internationally. 340 00:17:51,800 --> 00:17:55,320 Speaker 3: And you know, we've driven over two hundred almost two 341 00:17:55,400 --> 00:18:00,800 Speaker 3: hundred million fully autonomous miles, and we're driving over four 342 00:18:00,840 --> 00:18:02,880 Speaker 3: million miles per week, and. 343 00:18:02,800 --> 00:18:05,720 Speaker 4: So that's if you think about it, that's over. 344 00:18:05,760 --> 00:18:10,520 Speaker 3: Six human lifetimes every seven days. And so our driver 345 00:18:10,840 --> 00:18:14,040 Speaker 3: is learning at a rapid piece. So we don't think 346 00:18:14,119 --> 00:18:16,800 Speaker 3: there's anyone who's doing anything close to what we're doing, 347 00:18:16,840 --> 00:18:19,040 Speaker 3: and so for us, it's just staying focused on our 348 00:18:19,080 --> 00:18:19,879 Speaker 3: own ambitions. 349 00:18:20,280 --> 00:18:20,760 Speaker 1: Safety. 350 00:18:21,520 --> 00:18:24,640 Speaker 2: There are still concerns, and in January in particular, there's 351 00:18:24,680 --> 00:18:29,400 Speaker 2: two kind of again case studies of regulatory scrutiny right 352 00:18:29,400 --> 00:18:32,000 Speaker 2: of two specific incidences, and I think it's important for 353 00:18:32,080 --> 00:18:34,960 Speaker 2: both of them. I take time in putting it to 354 00:18:35,000 --> 00:18:37,399 Speaker 2: you and explain to you. But in the case of 355 00:18:37,440 --> 00:18:41,080 Speaker 2: the Santa Monica incident, for example, a way more vehicle 356 00:18:42,359 --> 00:18:46,520 Speaker 2: struck or collided with a child, but the system detected 357 00:18:46,520 --> 00:18:52,080 Speaker 2: the child. It breaked sharply, and at the point that 358 00:18:52,200 --> 00:18:54,760 Speaker 2: the impact was made, it was a speed of single 359 00:18:54,800 --> 00:18:58,600 Speaker 2: digits miles per hourably six it had been traveling at seventeen. 360 00:18:58,720 --> 00:19:03,920 Speaker 2: So in that instance the system worked, but a probe 361 00:19:04,040 --> 00:19:04,600 Speaker 2: was opened. 362 00:19:04,800 --> 00:19:06,760 Speaker 1: Just would you reflect on that. 363 00:19:07,480 --> 00:19:11,720 Speaker 2: But also, you know, my interpretation of what WEIMOS publicly 364 00:19:11,760 --> 00:19:13,679 Speaker 2: stated about this is that you actually kind of welcome 365 00:19:13,760 --> 00:19:16,920 Speaker 2: the opportunity to open up the system to the regulators, 366 00:19:17,200 --> 00:19:18,040 Speaker 2: let them look at it. 367 00:19:18,320 --> 00:19:22,480 Speaker 3: Yes, so, first and foremost, this was a child, and 368 00:19:22,600 --> 00:19:26,560 Speaker 3: we are extremely happy that she walked away from this incident. 369 00:19:27,520 --> 00:19:30,760 Speaker 3: As you said, because there's you know, an investigation pending, 370 00:19:30,760 --> 00:19:32,399 Speaker 3: we thought it was important to become a party to 371 00:19:32,440 --> 00:19:36,080 Speaker 3: the investigation, and so we're doing that. And as we've 372 00:19:36,119 --> 00:19:40,080 Speaker 3: already stated, you know, our car was traveling sixteen miles 373 00:19:40,080 --> 00:19:41,360 Speaker 3: per seventeen miles per hour. 374 00:19:41,600 --> 00:19:43,520 Speaker 4: We did detect her, you. 375 00:19:43,480 --> 00:19:48,080 Speaker 3: Know, coming between from behind a tall suv into the roadway. 376 00:19:48,320 --> 00:19:50,480 Speaker 4: We heartbreaked and we made. 377 00:19:50,280 --> 00:19:55,240 Speaker 3: Contact at six miles an hour, and we also determined 378 00:19:55,280 --> 00:19:58,480 Speaker 3: and our human equivalent model that human would not have 379 00:19:58,560 --> 00:20:03,080 Speaker 3: been able to perform as our superhuman driver performed. And 380 00:20:03,119 --> 00:20:06,720 Speaker 3: so this is an example we believe of exactly why 381 00:20:06,760 --> 00:20:08,960 Speaker 3: we do what we do. We want to make roads safer, 382 00:20:09,359 --> 00:20:12,520 Speaker 3: and we welcome the opportunity to cooperate with the NTSB 383 00:20:12,640 --> 00:20:13,520 Speaker 3: and this investigation. 384 00:20:13,880 --> 00:20:17,680 Speaker 2: Separately, safety investigators are looking at the issue of how 385 00:20:17,720 --> 00:20:22,679 Speaker 2: the WEIM interacts with parked school buses. This seems to 386 00:20:22,720 --> 00:20:26,960 Speaker 2: be sort of a separate technical challenge and what is 387 00:20:27,000 --> 00:20:30,720 Speaker 2: that about. Why is it that the weaiymos system has 388 00:20:30,840 --> 00:20:34,120 Speaker 2: to I guess struggles with is the is the headline 389 00:20:34,160 --> 00:20:37,080 Speaker 2: that came out, but with a parked vehicle of that 390 00:20:37,200 --> 00:20:40,000 Speaker 2: size in a school zone of course, where you have 391 00:20:40,160 --> 00:20:42,480 Speaker 2: mixed foot traffic of children in particular. 392 00:20:43,240 --> 00:20:46,120 Speaker 3: Yeah, I think you know, first and foremost, with safety 393 00:20:46,160 --> 00:20:48,879 Speaker 3: being our priority, how we perform around school buses and 394 00:20:48,960 --> 00:20:52,800 Speaker 3: children is a top priority for our company. You know, 395 00:20:52,840 --> 00:20:58,199 Speaker 3: we've already addressed this situation with software release, which is 396 00:20:58,240 --> 00:21:01,040 Speaker 3: really important to us. But also we partnered with the 397 00:21:01,080 --> 00:21:04,360 Speaker 3: Austin Independent School District, Yes to look at data they have. 398 00:21:04,560 --> 00:21:06,920 Speaker 3: So we can make sure that we are learning from 399 00:21:06,920 --> 00:21:09,800 Speaker 3: what they have. You know, their data obviously would be 400 00:21:09,840 --> 00:21:13,119 Speaker 3: more based on human driven vehicles, but still having that 401 00:21:13,200 --> 00:21:15,880 Speaker 3: opportunity to learn is really important to us. And then 402 00:21:16,000 --> 00:21:19,399 Speaker 3: once again, we have agreed with the NTSB to be 403 00:21:19,440 --> 00:21:22,000 Speaker 3: a party to this investigation because we think it's important 404 00:21:22,040 --> 00:21:25,240 Speaker 3: for us to understand for them to understand what we're seeing, 405 00:21:25,600 --> 00:21:29,520 Speaker 3: because we also have a lot of awareness around the 406 00:21:29,560 --> 00:21:30,320 Speaker 3: school buses. 407 00:21:31,320 --> 00:21:34,679 Speaker 2: If we call that an edge case interaction with the 408 00:21:34,680 --> 00:21:39,000 Speaker 2: school bus. That software fix that you talked about, is 409 00:21:39,000 --> 00:21:41,040 Speaker 2: it a total fix? In other words, it's way more 410 00:21:41,119 --> 00:21:44,920 Speaker 2: believe it's now solved that technical challenge. 411 00:21:45,160 --> 00:21:47,479 Speaker 3: I don't think we can think of it as a 412 00:21:47,520 --> 00:21:51,639 Speaker 3: single thing, okay, and I want to be super respectful 413 00:21:51,680 --> 00:21:54,760 Speaker 3: of the investigation here and so, but I don't think 414 00:21:54,760 --> 00:21:57,080 Speaker 3: we should think of it as a thing because you know, 415 00:21:57,240 --> 00:22:00,719 Speaker 3: there are angles, there are times they're not all parked, 416 00:22:00,760 --> 00:22:04,000 Speaker 3: and so I think we should let the investigation play 417 00:22:04,040 --> 00:22:06,240 Speaker 3: out and then happy to. 418 00:22:06,200 --> 00:22:07,320 Speaker 4: Talk to you afterwards. 419 00:22:07,880 --> 00:22:10,480 Speaker 2: There was a big sort of technological development which was 420 00:22:10,480 --> 00:22:15,960 Speaker 2: with GENI three. You know, the use of simulation. How 421 00:22:16,040 --> 00:22:19,400 Speaker 2: much has that kind of accelerated that the technology development 422 00:22:19,760 --> 00:22:21,680 Speaker 2: side of what Weimo's doing of late. 423 00:22:22,600 --> 00:22:26,199 Speaker 3: I think it's really exciting for us and something that 424 00:22:26,240 --> 00:22:31,720 Speaker 3: we continue to partner with the research teams. But really 425 00:22:31,760 --> 00:22:34,280 Speaker 3: our acceleration hasn't been dependent on that. 426 00:22:35,800 --> 00:22:39,919 Speaker 2: WEIMO has always talked about safety in the context of redundancy. 427 00:22:40,000 --> 00:22:40,240 Speaker 1: Right. 428 00:22:40,320 --> 00:22:47,800 Speaker 2: It's a multisensor suite around the vehicle, camera, vision, leder radar, 429 00:22:49,119 --> 00:22:53,080 Speaker 2: Tesla's approach, and they are at much smaller scale, especially 430 00:22:53,200 --> 00:22:56,520 Speaker 2: in the vehicles that no longer have a safety supervisor. 431 00:22:56,960 --> 00:23:00,760 Speaker 2: Is a vision only approached and you are trying to 432 00:23:00,800 --> 00:23:04,960 Speaker 2: scale in all of these cities? Is the different technology 433 00:23:05,280 --> 00:23:09,000 Speaker 2: Are the different technology approaches something that worry you based 434 00:23:09,040 --> 00:23:12,680 Speaker 2: on your belief of the kind of redundancy that's required. 435 00:23:14,240 --> 00:23:16,840 Speaker 3: No, it doesn't worry me. We have a lot of 436 00:23:16,880 --> 00:23:18,200 Speaker 3: conviction about our approach. 437 00:23:18,520 --> 00:23:18,639 Speaker 1: Right. 438 00:23:19,400 --> 00:23:22,480 Speaker 3: Our approach is what allowed us in October of twenty 439 00:23:22,520 --> 00:23:25,760 Speaker 3: twenty to remove the human driver from behind the wheel, 440 00:23:26,200 --> 00:23:28,800 Speaker 3: and it's what's allowed us to be the only company 441 00:23:28,920 --> 00:23:31,320 Speaker 3: to scale to over four hundred thousand trips per week. 442 00:23:32,680 --> 00:23:35,160 Speaker 3: If you can see and smell, and taste, in touch 443 00:23:35,200 --> 00:23:38,760 Speaker 3: and have all of your senses, why wouldn't you, and 444 00:23:39,080 --> 00:23:42,159 Speaker 3: especially with a safety critical function, We think it is 445 00:23:42,359 --> 00:23:46,160 Speaker 3: very important in the early days, especially to make sure 446 00:23:46,200 --> 00:23:49,359 Speaker 3: you're taking in as much data as possible to inform 447 00:23:49,400 --> 00:23:54,360 Speaker 3: the models and then to achieve the outcomes, and then 448 00:23:54,440 --> 00:23:57,640 Speaker 3: we can all debate, you know, how you go forward 449 00:23:57,720 --> 00:24:00,600 Speaker 3: from there. But this has been critical to our approach 450 00:24:00,600 --> 00:24:03,000 Speaker 3: and it's allowed us to scale, and it's allowed us 451 00:24:03,000 --> 00:24:06,479 Speaker 3: to achieve these safety results of a ninety percent fewer 452 00:24:06,880 --> 00:24:10,720 Speaker 3: serious injury causing crashes, and that is how you evaluate 453 00:24:10,760 --> 00:24:13,320 Speaker 3: whether or not this approach is working. And I know 454 00:24:13,359 --> 00:24:15,560 Speaker 3: there's a lot of discussion around costs, right. 455 00:24:15,480 --> 00:24:18,040 Speaker 1: Especially when you think about the economics at scale. 456 00:24:17,760 --> 00:24:20,520 Speaker 3: The economics at scale, So of course we're laser focused 457 00:24:20,560 --> 00:24:22,440 Speaker 3: on bringing these costs down. If you have to bring 458 00:24:22,480 --> 00:24:25,560 Speaker 3: the cost down once you achieve the safety because how 459 00:24:25,640 --> 00:24:28,639 Speaker 3: else do you actually know what the investment model for 460 00:24:28,680 --> 00:24:31,920 Speaker 3: the businesses if you haven't actually achieved the safety bar. 461 00:24:32,280 --> 00:24:34,199 Speaker 3: And so that's what we are focused on. Achieving the 462 00:24:34,240 --> 00:24:36,520 Speaker 3: safety bar. Now we can drive the cost down because 463 00:24:36,520 --> 00:24:36,800 Speaker 3: we know. 464 00:24:36,800 --> 00:24:37,439 Speaker 4: What it takes. 465 00:24:38,080 --> 00:24:40,920 Speaker 2: So let's end by me asking you this, in case 466 00:24:40,960 --> 00:24:43,119 Speaker 2: I don't speak to you for another year. In a 467 00:24:43,240 --> 00:24:47,719 Speaker 2: year's time, what are the metrics by which you, as 468 00:24:47,760 --> 00:24:51,000 Speaker 2: a leader in this company, will have judged success. You 469 00:24:51,040 --> 00:24:54,159 Speaker 2: know you plan to launch in twenty cities, but you 470 00:24:54,240 --> 00:24:58,240 Speaker 2: often point to different safety metrics and the miles driven internally, 471 00:24:58,320 --> 00:25:00,399 Speaker 2: What are you going to be holding the team to 472 00:25:00,440 --> 00:25:00,920 Speaker 2: account on. 473 00:25:01,840 --> 00:25:04,080 Speaker 3: By the end of twenty twenty six, we will be 474 00:25:04,200 --> 00:25:08,040 Speaker 3: doing over one million trips per week, and we will 475 00:25:08,080 --> 00:25:09,680 Speaker 3: be doing that across a host of. 476 00:25:09,680 --> 00:25:11,600 Speaker 4: US paid trips, paid trips. 477 00:25:11,760 --> 00:25:15,200 Speaker 3: We only talk about paid trips, and so we will 478 00:25:15,240 --> 00:25:18,439 Speaker 3: be doing over one million paid trips per week by 479 00:25:18,440 --> 00:25:19,720 Speaker 3: the end of this year, and. 480 00:25:19,640 --> 00:25:21,680 Speaker 1: That's the measurement of success in the nartime. 481 00:25:21,840 --> 00:25:24,920 Speaker 3: It's one of them, I think do having the safety 482 00:25:24,960 --> 00:25:28,400 Speaker 3: culture that we've had within the company. 483 00:25:28,720 --> 00:25:32,120 Speaker 4: It permeates through the data, but it starts. 484 00:25:31,680 --> 00:25:35,280 Speaker 3: With how we are so disciplined about what we do 485 00:25:35,359 --> 00:25:37,520 Speaker 3: and how we do it. It matters a lot to us, 486 00:25:37,840 --> 00:25:40,240 Speaker 3: and so making sure that we have that culture intact, 487 00:25:40,280 --> 00:25:42,120 Speaker 3: I think is the other way that we will continue 488 00:25:42,119 --> 00:25:43,560 Speaker 3: to measure our success.