Waymo and the Rise of the Robotaxis | To Build a Driver | 1

0:08It's December 2024, and in Phoenix, Arizona, Mike Johns is trapped inside a driverless taxi. Johns Waymo has arrived at his destination, the airport terminal, but instead of stopping to drop him off, the vehicle keeps looping through the parking lot over and over. The robo-taxi is now on its sixth lap of the lot, and Johns can't open the doors. If he can't get out soon, he'll miss his flight. Hi there, Mike. This is Gab. I'm calling from Waymo Support. I'm just calling because I received a notification with your car might be experiencing some routing issue. Please bear with me while I am... Yeah, I got a flight to catch.

0:49Why is this thing going in a circle? I'm getting dizzy. The Waymo representative tells Johns to try using the stop command on the Waymo app. I don't have an option to control the car. Oh, my gosh. After several minutes, the representative finally finds a way to stop the ride. Johns bolts for the terminal, shaken, and vowing never to ride in a robo-taxi again. But in a growing number of U.S. cities, passengers don't have this choice. A tap in an app might summon a human driver or a car with no driver at all. And leading this driverless revolution is Waymo, Google's 20-year quest to build not a car, but a driver.

1:33Waymo says its vehicles have now driven more than 100 million autonomous miles. That's the equivalent of traveling to the moon and back 200 times. But this journey has cost Google's parent company Alphabet billions, with profits still somewhere over the horizon. And the competition, Tesla, Amazon Zoox, and China's Baidu is closing in fast, betting that speed, not caution, will win the race. But is this the dawn of a trillion-dollar industry? or just another sparkly Silicon Valley mirage?

2:18From Wondery, I'm David Brown, and this is Business Wars.

2:46You know, driverless taxis have been promised for years, and now that promise is finally starting to take shape. Today, in cities like Phoenix, Los Angeles, and Shanghai, people can hail rides with no one behind the wheel. Technology that once felt like science fiction has slipped into the everyday, in some places at least. But the journey has been long. It's been costly and full of wrong turns. And the next stretch may prove even more challenging. Building a car that can see and think like a human has proven to be far harder than even Google's engineers imagine. Mapping streets is one thing. Teaching AI how to react to emergency vehicles, spot chain-link fences, or respond to a construction worker waving traffic through the wrong lane.

3:37That's another matter. Even something as ordinary as a plastic bag drifting across the road can confuse the vehicle's cameras. And then there are the human hurdles. Regulators aren't sure who to ticket when a driverless taxi breaks the rules. Insurance companies can't agree on who's to blame when an accident occurs. and many passengers still aren't ready to trust an empty driver's seat. One recent poll found just 9 % of people said they trust a self-driving car, while 66 % actively fear them. Yet, despite all the uncertainty, the money keeps flowing. Billions of dollars have already been poured into bringing these vehicles to market.

4:20At the head of the pack is Waymo, the alphabet-owned pioneer that's been chasing autonomous driving for almost 20 years. The long, complicated push to create self-driving cars is a story of dreamers, geniuses, and painful double crossings. And the true winner of this race has yet to be determined. This is Episode 1, To Build a Driver.

4:51It's 2002 at the University of California, Berkeley. In a cluttered lab, a 22-year-old graduate student hunches over a desk scattered with circuit boards and toy parts, with a phone wedged between his ear and shoulder. His name is Anthony Lewandowski. He's Belgian, ambitious, and already known around campus as the kid who never sleeps. On a shelf behind him sits his latest creation, a small Lego robot that sorts Monopoly money by color. Sounds trivial, but that little robot has just won him a national robotics prize and a reputation as the campus prodigy who can build anything out of almost nothing.

5:33Lewandowski's on the phone with his mother in Brussels. She's just read an article about a new U.S. government competition, A million-dollar challenge that sounds almost impossible. The contest is run by a U.S. government agency, and it's offering a prize of$1 million for the first vehicle that can drive itself across the Mojave Desert. The contest has an exhilarating romantic name, The Grand Challenge. Lewandowski pauses. A driverless car. To most people, it sounds like science fiction. To Lewandowski, a bright engineering student who still believes that with enough intelligence and dedication, anything is possible, well, it sounds like an opportunity.

6:17The competition is the start of a journey that will pull him from Berkeley's labs into the heart of Silicon Valley and eventually into one of the fiercest rivalries in tech history. The agency behind this million-dollar competition is DARPA, the U.S. Department of Defense's secretive engine of innovation. Formed after the Soviet launch of Sputnik, DARPA's mission is to ensure America is never again caught technologically flat-footed. The Internet began as a DARPA project, and the agency has played a huge role in other technologies too, such as satellite navigation, voice assistants like Siri, and even the graphical interfaces that help make personal computing usable.

7:00Now, DARPA has turned its attention to driverless cars. The push comes from the war in Afghanistan, where U.S. troops are being killed by roadside bombs hidden along convoy routes. Congress wants to remove soldiers from harm's way wherever possible, and it has tasked DARPA with an ambitious goal. Build autonomous military vehicles by 2015. The grand challenge is DARPA's attempt to jumpstart this effort. It's a desert race open to anyone who can build a vehicle that drives itself nearly 150 miles across the Mojave. No remote controls, no human staring from afar. each vehicle must sense the world, make decisions, and drive on its own.

7:50Like many others, Lewandowski first considers building a car. But one day, riding through the California hills, a pack of motorcyclists whips past him, which sparks an idea. A motorcycle would be harder to automate than a car, far harder. But it would also set Lewandowski apart. DARPA wants bold ideas, and surely no one else is attempting to automate two wheels instead of four. If he can make a bike balance and steer itself through the desert, he won't just be another entrant. He'll be unforgettable. This is a masterclass in differentiation. Lewandowski knows he's an underdog with less money and fewer resources than the big teams.

8:39So instead of trying to beat them at their own game, he changes the game entirely. He picks a project so audaciously difficult that even if it fails, he'll succeed in separating himself from the herd. You know, in a crowded market, sometimes the riskiest move is actually the safest way to get noticed. With a rough plan in mind, Lewandowski joins forces with a small group of fellow UC Berkeley engineers who call themselves the Blue Team. They mount two cameras on the handlebars to function like a pair of eyes and strap a cluster of computers to the frame. The computers use the cameras to read the road, steer, and adjust the bike's balance.

9:19There's no one with a joystick standing in the background, no tether to a laptop. In theory, this bike can drive itself. In practice, however, it falls over. A lot. Hundreds of times, the bike topples, clattering onto the asphalt. And each time, Lewandowski hauls it upright, patches the damage, tweaks the programming, and tries once more. Every crash brings him one step closer to a self-driving motorcycle. He calls it Ghost Rider, a fitting name for a machine that seems haunted by its struggle to stay upright.

10:05It's March 2004, and in the Mojave Desert, the countdown to the start of the first Grand Challenge is underway. The starting line looks like something out of Mario Kart. Fifteen experimental vehicles are lined up in the dirt. Cars, trucks, and a single motorcycle. Each one promising to drive itself across nearly 150 miles of rough desert. Ghost Rider, Lewandowski's autonomous Yamaha, is the only bike in the field, and it looks wildly out of place even among the hulking four-wheelers beside it. A beige Humvee named Sandstorm idles nearby. It was built by a team from Carnegie Mellon University in Pittsburgh, including a young roboticist named Chris Urmson.

10:52Unlike Lewandowski's camera-based system, the Carnegie Mellon crew relies on something new, LiDAR. That stands for Light Detection and Ranging. And it's a sensor that fires thousands of laser pulses a second, measuring how long each takes to bounce back. LIDAR allows Sandstorm to build a three-dimensional map of the world in real time. The Marshal waves a flag and the robotic vehicles lurch forward. Chaos ensues. One truck veers into a barrier. Another plows into a ditch. A third clips a fence post and flips over. Lewandowski's Ghost Rider wobbles for a few heroic seconds, then tips over right at the starting line.

11:37By the end of the first mile, one vehicle is on its side and another's tangled in barbed wire. By mile 7, only Carnegie Mellon's Sandstorm is still moving. But soon, even the Humvee finds itself stranded on a mound of dirt, its wheels spinning helplessly. By the time the race is over, not a single vehicle has finished the course. Sandstorm made it the furthest, 7.4 miles. But despite his bike's failure, Lewandowski stood out to one spectator for his ingenuity and persistence. That spectator is the founder of Velodyne, a small California firm that wants to develop LIDAR for future autonomous vehicles.

12:21Velodyne's founder hires Lewandowski as a salesman with engineering know-how. Hmm. See what happened there? In the corporate world, we're often terrified of failure, but in the startup world, a spectacular, ambitious failure is often worth more than mediocre success. Velodyne didn't hire Lewandowski for the result. The bike fell over, after all. They hired him for his hustle. In other words, they bought the engineer, not the engine. When someone's looking for talent, they may not be looking for the win as much as the will to make big things happen.

13:03A few days later, a small group of engineers from Carnegie Mellon's Sandstorm team is at the AM General Campus in South Bend, Indiana. That's the birthplace of the Humvee. They're here to show the heavy vehicle maker what their robot truck can do. If the demo goes well, they'll walk away with free parts and maybe even a Humvee or two they can use for tests. Inside a nearby conference room, one team member is giving a PowerPoint presentation about their technology to a group of AM General executives. Outside in the parking lot, two teammates are prepping Sandstorm for the demonstration with a few test runs.

13:41Sandstorm's goal today seems simple. navigate an obstacle course designed to teach new Humvee owners what their vehicles can handle. The course includes a concrete tabletop structure that stands about 18 inches off the ground. Sandstorm is supposed to drive itself up and onto that structure. One of the engineers looks up from his computer, then signals to his colleague, All right, system's online. Let's do this. His colleague stands ready with a remote kill switch, a failsafe in case the vehicle goes rogue. Copy that. Okay, here we go. Sandstorm's engine growls to life. The robo-humvee jolts forward, a little faster than expected.

14:25Whoa there, ease it up, buddy. But Sandstorm doesn't ease up. It accelerates. The engineer hammers the kill switch, but the signal takes a couple of seconds to reach the vehicle. Sandstorm slams straight into the concrete block, leaving a dent big enough to slip a fist into. The engineers scramble to check for damage. The sensors are intact, bumpers scuffed, but the Humvee can still drive. They restart it for a second run. This time, Sandstorm is supposed to swing wide, away from the barrier. Instead, its wheels turn sharply toward the building, where A.M. General's executives are still listening to the PowerPoint pitch.

15:08No, not that way. Kill it! Hey! Too late. Sandstorm plows into the side of the building with a metallic thud that shakes the windows. The executives spring from their chairs and rush outside to find the robotic Humvee idling against the wall, a fresh scrape in its bodywork. The Carnegie Mellon team braces for disaster and a long drive home. But the executives just laugh. A.M. General built the Humvee to push limits, and that's exactly what the Sandstorm team is doing. An executive strides over to the group. Okay, boys, okay, we'll give you two Humvees. Just, look, be careful with these ones, okay?

16:00It's October 2005, 18 months after the chaos of the first DARPA Grand Challenge. And now, a new lineup of driverless vehicles is seeking glory. This time, 23 teams are lined up outside Prim, Nevada, ready to send their robots across 132 miles of dust, rock, and canyon. The Carnegie Mellon crew, including Chris Urmson, is back with the latest incarnation of Sandstorm, their automated Humvee. They're eager to prove that last year's crashes were just the beginning of something bigger. But they're not the only ones with something to prove. Their toughest competition is Stanley, a gleaming VW Touareg built with corporate backing from Volkswagen's research labs in Palo Alto.

16:49At the center of Stanley's team stands Sebastian Thrun, a 38-year-old Stanford professor with a boyish smile. He's a German-born roboticist, obsessed with machine learning, and has spent years teaching computers to understand the real world. Volkswagen sees the project as a way to prove that its engineers can compete with Silicon Valley's brightest minds. For AM General, which still supports the Carnegie Mellon team, it's about demonstrating that its Humvees can handle anything. And for DARPA, this race is still an experiment, One it hopes will lead to military vehicles ferrying weapons and supplies without the need for human occupants.

17:31It's science with big stakes. The prize pot has now doubled to$2 million. But whoever makes a well-functioning autonomous vehicle first won't just win the cash. They'll potentially own the future of transportation. The race begins. Engines roar, dust clouds bloom, and one by one the vehicles head into the desert. This time, something extraordinary happens. Instead of collapsing after a few miles, nearly every team's robot vehicle makes real progress. Machines that just 18 months earlier wobbled and crashed now carve perfect turns, break on slopes, and weave around boulders. All but one of the 23 entrants beat the seven-mile record set by Sandstorm last year.

18:24Five complete the entire course. But the prize comes down to two contenders, Sandstorm and Stanley. Sandstorm finishes second. Stanley crossed the line just 11 minutes faster. Among the spectators lining the Nevada hills is one Larry Page, the co-founder of Google. He's not just here for fun. He's come to scout talent. The morning after the DARPA Grand Challenge, Sebastian Thrun is a hero. His modified Volkswagen, Stanley, has just driven 132 miles of desert terrain without human intervention. A breakthrough that's caught the eye of Google's co-founder. Page asks Thrun to visit Google's headquarters in Mountain View, California.

19:13It's the first of dozens of meetings at Googleplex, in which the pair discuss and debate the promise of self-driving cars and how they just might change the world. To Page, this technology isn't just a stunt. It's the next step in Google's corporate mission to organize the world's information. He believes that the most chaotic, dangerous information system on Earth is traffic. Autonomous cars, he says, could eliminate human error on the roads and reduce crashes by as much as 90%. And he wants Thrun to help Google make that happen. Thrun listens with mounting irritation. The DARPA races took place on a controlled desert course, where there were no pedestrians, no delivery vans blocking the lane, no road work, no traffic lights.

20:06But the real world is different. It's unpredictable. Messy. alive. Thrun tells Page that trying to build a robot that can handle this chaos is madness. Page doesn't blink. He asks for a technical reason not to pursue autonomous driving. Thrun loses his temper, yelling, it can't be done, goddammit!

20:32This right here is the friction between a manager and a visionary. A manager looks at the current capabilities and sees roadblocks. A visionary like Page looks at the ultimate destination and ignores the road entirely. Page isn't interested in better. He's interested in different. He's reframing the problem from how do we map the world to how do we fix the driver? And usually, the person asking the impossible question is the one who ends up owning the future. Thrun leaves the meeting, fuming. He spends the night searching for undeniable proof that what Page wants is impossible. But by morning, he has nothing.

21:21It's three years later. At Lake Tahoe, Thrun has gathered a small group of brilliant engineers to witness the birth of a secret project that will become Google's self-driving car division. Chris Urmson, the calm Canadian engineer from Carnegie Mellon, whose Humvee Sandstorm came in second in the DARPA race, is the project's technical lead. He's responsible for turning their prototypes into something that can drive on real roads. Anthony Lewandowski, the restless entrepreneur from Berkeley who built the Ghost Rider motorcycle, focuses on the hardware systems. His job is to make all the sensors, cameras, software, computers, engines, maps, and brakes work together as a coherent system.

22:05Thron will guide the overall vision and ensure the project balances ambition and caution. Around the three men sit a handful of roboticists, AI specialists, and map engineers from across Google, the sort of people Larry Page handpicks for projects too sensitive to speak about and too bold to fit anywhere in the company's normal structure. The group debates the challenge ahead. How do you make a machine that not only drives, but thinks and reacts? Thrun tells them they're not building a robot car, they're building a driver. This insight becomes their North Star. The goal isn't to retrofit a vehicle or design roadside sensors or build control towers.

22:50Their goal is to put intelligence inside the car. But before they can build anything, they have to agree on what kind of project this is going to be. Larry Page has already signaled that he wants it done inside Google, where it can be protected, funded, kept out of sight. For the engineers gathered at Tahoe, this is a relief. Only a company with Google's resources could afford the computing power, mapping data, and sheer volume of time needed to make a self-driving car possible. They give it a name that nods to the ambition to replace, not assist, the human behind the wheel. Project Chauffeur.

23:33Within months, the team begins testing modified Toyota Priuses around Mountain View, each topped with a spinning LiDAR dome. To passersby, they look like odd prototypes, some sort of lab equipment on wheels. But inside Google, they represent something utterly revolutionary. A mission to end the era of human drivers.

24:23The Project Chauffeur team is finally ready to move from theory to asphalt. Google co-founder Larry Page has given them a simple but brutal target, and he's put real money behind him. If the Project Chauffeur team can successfully have an autonomous car drive 1 ,000 miles of complex California roads, or 100 ,000 miles total within two years, Page has promised the engineers enormous bonuses. The milestone becomes known as Larry's 1K. Thrun, Urmson, and Lewandowski start by breaking the task into pieces. Instead of one long route, they design a patchwork of 10-mile segments, each one chosen to challenge the project's driving software in a different way.

25:11They choose a stretch of freeway to assess its merging and lane-keeping, a climb into the Santa Cruz Mountains to teach it how to brake on hills, and a run through the famously windy Lombard Street in San Francisco involving eight hairpin bins packed into a single city block to see if their machine can manage chaos. Ridges, tunnels, intersections, roundabouts, each segment becomes a new test of judgment, timing, and perception. For a human, these moments are instinctive. For a machine, they're puzzles to be solved. This is the classic answer to the question, how do you eat an elephant? Perhaps you've heard this one before.

25:56One bite at a time. See, if you give a team a massive vague goal like build a robot driver, chances are they'll freeze. But if you break it down, you turn an impossible mountain into a series of climbable steps. These small wins keep the momentum going, especially when the finish line seems like it's still miles away. Day after day, the project chauffeur team loads up their modified Toyota Priuses and sends them out onto California's back roads with their spinning LiDAR domes capturing 3D maps of the world around them. Each time they tweak the car's software, the car manages to drive a little farther before handing control back to the human in the driver's seat.

26:42The gains are incremental. This isn't a project built around major breakthroughs, but one that advances steadily, slowly. By breaking the problem to small, repeatable challenges, the engineers are doing something no one has done before. They're teaching a robot to handle the road not as a controlled experiment, but as real life, unpredictable, messy, human.

27:14At night, the engineers work late, taking their modified Toyota Priuses around the streets near the Google campus. The cars hum through the dark with spinning LiDAR domes on their roofs, alien shapes gliding past convenience stores and sleeping suburban homes. Officially, Project Chauffeur doesn't exist. Secrecy is paramount. The handful of people who do know about it refer to it only by codename. The rest of Google has no idea that the multi-billion dollar company they work for is quietly teaching cars to drive themselves right outside its own parking lot. But every trip beyond Google's campus brings the risk of exposure.

28:01One night, near Shoreline Boulevard, a five-minute walk from Google HQ, Two engineers pull over to adjust a sensor. They crouch beside the modified Prius and hook the car up to their laptop through cables that snake across the curb. But then, blue lights flash behind them. A Mountain View police officer steps from his cruiser. He looks from the open laptop to the spinning laser dome on the vehicle and demands to know what the two men are doing. For a moment, neither engineer speaks. Google's top-secret project is about to be blown open by a night patrolman. Then, one of the engineers straightens up, smiles, and in Russian-accented English, calmly tells the cop they work for Google.

28:50The officer studies them, shrugs,