Waymo Slams Tesla's Camera-Only Self-Driving Strategy as 'False Summit' After 200M Miles

In a swipe at Tesla, Waymo says 'cameras... aren't enough'

As Tesla gears up for the official launch of its steering wheel and pedal-less Cybercabs, Waymo is issuing a stark warning about Elon Musk's approach autonomous driving. Srikanth Thirumalai, Waymo's VP of Onboard Software, doesn't specifically call out Musk or Tesla in a blog post, published Wednesday, entitled "10 AI Lessons from Driving 200+ Million Fully Autonomous Miles." But his intention is clear: Tesla's system is insufficient to the task of fully autonomous driving. "Cameras are incredible, but they aren't enough," Thirumalai writes. "For years, there's been a debate over whether cameras alone could solve full autonomy. Now, after more than 200 million real-world miles, the data is clear: safe, fully autonomous operations at scale require more." Waymo uses cameras, in addition to lidar and radar, to create "a rich, redundant world view that no single sensor can replicate," he adds. Musk, of course, would beg to differ. The occasional trillionaire has over the years made his distaste for lidar widely known, calling the laser-based sensor "a crutch" and predicting that any company relying on the powerful but expensive tech is "doomed." The crux of his argument is that humans make driving decisions primarily through the use of their eyes, so why not autonomous vehicles? Of course, Tesla is mostly alone in this position. The vast majority of AV operators, from Waymo to Zoox to Motional, use lidar, in addition to radar and camera, as part of their on-board suite of sensors. They believe that autonomous vehicles need to be better than humans with regard to their perception systems, which requires a redundant multi-sensor approach. If one sensor fails, the vehicle wouldn't be fully blinded as other sensors can help guide it to safety. Tesla's camera-only approach could shut it out of certain markets, depending on how certain policy debates turn out. New Jersey's state legislature is currently considering a bill that would legalize robotaxis, but only if they include multiple sensors. Tesla would be banned under such a law. Thirumalai goes on to outline other differences between Waymo and Tesla. While Musk thinks the use of high-detail maps to help chart an autonomous vehicle's course is "a really bad idea," Waymo believes that HD maps are a powerful "prior." Waymo uses HD maps to "jump-start our validation process, so we can provide a fully autonomous service to riders from our first trip," Thirumalai says. "As we drive, we treat our maps as another input -- like our sensors, but acting as a mental memory." Musk believes autonomous vehicles need to be able to drive without a map; after all, roads change, lanes get repainted, construction zones appear, as do potholes. Musk believes that you need an instant analysis system that's so good it gains little from maps -- and that HD maps in particular can slow down the development of that necessary system. But Waymo isn't resting on its mapping laurels. The robotaxi company uses an AI-driven mapping system to ensure its maps are "continuously updated," Thirumalai writes, "providing the vehicle with a reliable, high-fidelity reference to lean on during complex maneuvers." In other words, mapping is useful, but it's not an end-all-to-be-all. Thirumalai goes on to describe some of Waymo's other principles -- closed-loop simulation can help identify more edge cases, Vision-Language Models are great reasoning tools -- before concluding with his most direct swipe at Tesla yet: you can't build a fully autonomous system on a Level 2 driver assist one. This, of course, gets at the heart of the Tesla proposal: that with enough data and enough miles and enough training, eventually its advanced driver assist systems, Autopilot and Full Self-Driving (Supervised), will evolve into Level 4 capable, fully autonomous platforms. Today, Tesla's FSD system is still classified as a Level 2 system, meaning drivers need to monitor the driving at all times and be ready to take control at a moment's notice. If a crash occurs while FSD is being used, Tesla will always blame the driver, claiming that the company's terms of service require constant driver monitoring. But that's not how Musk and other executives talk about FSD. In fact, Tesla was forced to add "Supervised" to its marketing materials after regulators complained that the company was misleading customers. So who's right? Waymo or Tesla? Waymo operates its fully autonomous vehicles in 11 cities, conducting 500,000 paid trips a week. Tesla has its own robotaxis, some of which are supervised by human safety drivers, but an increasing number of which are unsupervised. And the company is on the cusp of launching its purpose-built Cybercab - though its unclear how widespread it will be at launch. But after boasting about his company's autonomous capabilities for years, Musk is still very clearly trailing behind Waymo. It's unlikely he's going to suddenly shift his tactics to embrace lidar, but he is undoubtedly aware that he is lagging behind Alphabet's robotaxis. What he plans on doing about that will become increasingly clear in the months ahead.

Waymo Takes A Not-So-Subtle Shot At Tesla's Self-Driving Strategy

* In a new blog post, Waymo laid out 10 takeaways from 200 million miles of autonomous operation. * It took some swipes at Tesla's approach to developing self-driving tech. * Waymo casted doubt on camera-only systems, end-to-end AI, and improving a Level 2 system to full autonomy. Waymo didn't name Tesla in its latest blog post. But it didn't really have to. The two companies have spent years pursuing radically different visions of what self-driving technology should look like. And on Wednesday Waymo made it abundantly clear which it thinks will win. In the post, the company's vice president of onboard software, Srikanth Thirumalai, laid out 10 learnings from 200 million autonomous miles. Without mentioning any rivals by name, Waymo effectively picked apart the key tenets of Tesla's self-driving philosophy. For starters, Waymo addresses the elephant in the room: the sensor question. Tesla uses only cameras, and Elon Musk has called lidar a "fools errand." Waymo's latest system in its Ojai van, by contrast, relies on 13 cameras, 4 lidar units, and 6 radars, plus microphones. Thirumalai writes that "multimodal sensors are indispensable" and takes direct aim at the vision-only approach. "Cameras are incredible, but they aren't enough," he says. "By combining inputs from cameras, lidar, and radar, the Waymo Driver creates a rich, redundant world view that no single sensor can replicate." Lidar sensors, he explains, "capture 3D geometry with millimeter precision." Radar tracks velocity and detects objects in conditions that cameras can't, like in heavy fog. Cameras, he says, are good for reading street signs and traffic lights. Thirumalai also notes the importance of HD maps, which Tesla says it doesn't need. The highly detailed maps, he says, are "incredibly helpful in poor visibility and complex thoroughfares." And he casts doubt on end-to-end AI systems that take in sensor data at one end and spit out driving instructions at the other. This idea is core to Tesla's approach, and it's been adopted by others in the space too. "Pure end-to-end (E2E) neural architectures, where a model takes in raw pixels and directly outputs steering commands, run the risk of black box failures," he says. "That means, it's hard to understand how decision making happens in full E2E systems." Tesla has for years promised that Full Self-Driving (Supervised) would eventually get so good that it could take the human out of the loop. That the vast trove of FSD data collected from Tesla's customer fleet would help it get to true autonomy. But Waymo argues that to really improve an autonomous system, you need to have it operate autonomously. "Simply improving a driver-assist system (L2) for full autonomy is a false summit," Thirumalai says. "You can run billions of miles in simulation or with human supervision, but an AV system only truly matures when it is solely responsible for the driving task. Full autonomy exposes the system to the true gravity of its decisions and reveals novel situations that humans or simulations might unconsciously smooth over." It's not surprising that Waymo thinks its philosophy is the right one. Of course it does. But it's making that argument more explicitly than before, right as Tesla finally makes the inroads into autonomy that it's hyped up about for years. The company appears to have removed the safety operators from its Robotaxi service across several markets. It has scheduled a launch event for the purpose-built Cybercab for next week, though it's not clear what exactly that will entail. Tesla maintains that its more streamlined approach is easier to scale. But Waymo has the distinct scale advantage right now, with over 500,000 driverless trips per week. The next few years will show who's really got the edge.

Waymo takes a shot at Tesla's self-driving: it's a 'false summit'

Waymo published a list of "10 AI lessons" from driving more than 200 million fully autonomous miles, and several of them read as a direct rebuke of Tesla's self-driving strategy -- without ever naming Tesla. The sharpest: trying to turn a driver-assist system into full autonomy is a "false summit," according to Waymo. That's exactly what Tesla is attempting with Full Self-Driving. What Waymo actually said The post, published Tuesday by Waymo's head of AI foundations, Srikanth Thirumalai, frames all 10 lessons around safety and the company's 200-million-mile record in fully driverless operation. Lesson 10 is the one aimed squarely at the L2-to-L4 playbook: Simply improving a driver-assist system (L2) for full autonomy is a false summit. True L4 maturity can only be safely achieved by a purpose-built system, validated on closed courses and hardened by the uncompromising experience of driving without a human in the car. Waymo's argument is that neither billions of simulated miles nor millions of "supervised" human-present miles can replicate what a system learns once it operates with no human backup. That's a pointed contrast with Tesla, which trains FSD on data from a fleet of customer cars whose drivers remain legally responsible for the vehicle. Cameras alone and the 'black box' Two other lessons land in Tesla's lap. Lesson 1 states plainly that cameras alone can't deliver safe, full-scale autonomy, and that Waymo combines cameras, lidar, and radar for redundancy. Tesla runs a camera-only "Tesla Vision" stack -- a bet Waymo's co-CEO already picked apart earlier this month when he explained why camera-only self-driving falls short. Lesson 4 warns against pure end-to-end neural networks that convert raw camera input directly into steering commands: "You can't build trust with a black box." Tesla has spent the last two years selling exactly that end-to-end approach as the core of FSD v14 and v15. However, the approach often results in a two-step-forward, one-step-back situation with every new update. The widening gap behind the jab The confidence has numbers behind it. Waymo is now serving more than 500,000 paid, fully driverless rides every week across its US markets, and it has set a target of one million by the end of the year. Tesla, by comparison, still runs a small "Robotaxi" service that launched in Austin with human safety monitors in the car, and by some counts its fleet has shrunk rather than grown. CEO Elon Musk has promised "unsupervised" FSD would be widespread by year-end -- a target he has moved repeatedly. A year into the program, Tesla confirmed last month that it has driven only 380,000 unsupervised miles - something Waymo does in a day. Electrek's Take Waymo didn't name Tesla, but it didn't have to. Every one of these "lessons" maps onto a specific Tesla decision: camera-only sensing, an end-to-end black box, and, most pointedly, the belief that you can incrementally upgrade a consumer driver-assist product into a robotaxi. The "false summit" line is the interesting one and should ring true to anyone following Tesla's effort closely. CEO Elon Musk has declared victory so many times when it comes to solving autonomy and each time, it was indeed a false summit. Waymo is arguing that the hardest part of autonomy, the long tail of weird, dangerous edge cases, only reveals itself when there's no human to catch the mistakes. Tesla's approach assumes it can climb to that summit gradually, learning from millions of Teslas whose drivers are still doing the catching. Waymo is telling the market that path doesn't reach the real peak; it just gets you to a ledge that looks like one. Is Waymo right? I don't know. But it is certainly ahead of Tesla and scaling much faster. Its sensor fusion approach appears much more robust than Tesla's vision-only. Now, Tesla fans would argue that none of that matters because Tesla is on the verge of achieving generalization and would quickly overtake Waymo, if that's the case. But there's no clear evidence that's happening. If you've been thinking about solar, the best way to size it right is to compare a few competing quotes. To find a trusted, reliable solar installer near you that offers competitive pricing, check out EnergySage, a free service that makes it easy for you to go solar. It has hundreds of pre-vetted installers compete for your business, ensuring you get high-quality solutions and save 20 to 30% compared to going it alone. Plus, it's free to use and you won't get sales calls until you select an installer and share your phone number with them. And if you don't have the cash upfront, many installers offer $0-down solar leases and power purchase agreements (PPAs) so you can go solar for no money down. Your personalized solar quotes are easy to compare online and you'll get access to unbiased Energy Advisers to help you every step of the way. Get your free quotes here.