This seems to be wishful thinking on the part of Uber, and also Tesla. Google StreetView data is probably sufficient. Waymo's expansion into new cities does not seem to be delayed much by the need for more data.
Most of the reported problems with self-driving come from transient situations. More mapping data will not help with those.
China has the Beijing High-level Autonomous Driving Demonstration Zone, where traffic cams and other sensors let vehicles see beyond their own sightlines.[1] That's been going on since 2020. That's the ultimate in sensing - full real time road info.
The Beijing test area is getting some expansion. The new direction seems to be to focus on airports and railroad stations, so that driverless cars can be aware of congestion in detail. That makes sense.
[1] https://sinocities.substack.com/p/inside-chinas-connected-ve...
There's also a huge sunk R&D cost and an ongoing R&D cost that probably dwarfs operating costs. But the per-car cost drops as more cars are deployed.
On the other hand, robot vehicles can have higher utilization than single-owner vehicles. They can be on the road as long as there are customers. Observation of their parking lots indicates most of the cars are out on the road about 12 hours a day.
What I noticed about China is that they employ a lot of people to stand around in nice looking government (non-police) uniforms and do various menial work or not much at all.
The US does this to a perhaps a lesser extent with jobs like TSA agents.
Sure, I guess you can do UBI, but what if that’s less efficient overall?
Example given with made up numbers:
Status quo, an Uber driver makes $20/hour out of a revenue of $50/hour total covering vehicle operating costs and platform fees.
Self-driving cars: self-driving cars cost $40/hour to operate, UBI pays someone a wage of $20/hour since there’s no job available. This basically means that rideshares now cost $10/hour more to operate than before.
Or, maybe that person on UBI makes $10/hour instead of $20/hour and gets a worse job to cover the difference.
Obviously there are many flaws and assumptions with the way I present this scenario but it’s a really good question to bring up whether putting everyone out of work is actually going to be a net positive.
Regarding what you said about driver hours, it’s not unheard of to run multiple drivers on multiple shifts with the same vehicle. Not all rideshare drivers own the vehicle nor use it as a personal vehicle. But the other factor is that the drivers who do use personal vehicles effectively subsidize the fact that they can only drive it for a human-length shift. Waymo has to buy every car (more expensive than a normal car) and use it only for business purposes while an uber driver can just use the same used Toyota Prius they use to take their kids to soccer practice.
Unlike web services that giants like google provide (e.g search), waymo and other AVs essentially cannot fail. Like at all. It is suspectible to ‘randomness’ of nature that can be the difference between life and death.
A lot of so called ‘smart’ people are going to find themselves getting humbled by the real world.
Humans are able to make sense of the world around them through things like intuition. Machines do not possess this characteristic.
This is an extraordinary claim. Self driving cars just need 15 ft grid panoramic images that are months or years stale? What experience are you basing this claim on?
You can’t be the CTO of Uber wanting to do AVs, and get the data collection requirement shockingly wrong.
Waymo’s bottleneck has never been data. When they want data about a school intersection in SF at a certain time of day, they just... synthetically generate it and simulate: https://waymo.com/blog/2026/02/the-waymo-world-model-a-new-f...
Waymo is able to deploy with less (but targeted and high quality) data collection by having world class simulation capabilities. Not that they haven't collected huge amounts of data as it's no doubt important (I've heard their onboard storage is transferred and emptied every few days), it's just not a bottleneck. They have the most efficient operation in the AV industry.
The best example of why data collection isn’t the bottleneck is Tesla. They boast about billions of miles of data, yet they’re struggling to put out fully autonomous vehicles.
I think it's more about detecting changes to the world. You need boots on the ground, so to speak, to see that new speed limit sign or the new lane paint. The Waymo vehicle can no doubt react to changes in the world when it encounters them, relaying them back to the mothership, but it's better to know about them in advance.
It'll shock you to know that you can simply get this from governments, some even provide this in API form
I'd be surprised if this is a thing outside the biggest US (and European, for that matter) cities, judging from Google StreetView there are lots of streets in US cities/towns with almost no paint lines at all.
A human doesn’t need to be shown every single road that exists in order to drive.
One example, from the end of the journey: knowing in advance where the actual entrance to the business is, or the specific curb cut that leads to the residence, makes it easier and far less error prone to decide exactly where the journey should end. Even humans have a hard time figuring out the right access point for a business or residence. This is a job for an offline process, fed by as many data sources as possible.
Tesla on the other hand has billions of miles of data, yet because there is a limit to camera-only techniques, that data isn't that useful is it? They have no ground truth data to evaluate their camera system on, which is why sometimes you see those Teslas driving around with lidar rigs mounted on them. Going camera-only is just asking for trouble.
Of course, Waymo still has much more room for improvement. But it's much more efficient to supplement less but higher quality IRL data with large amounts of synthetic data, than to run a million data collection vehicles 24x7 because most IRL data is boring and useless.
Waymo said 6 years ago they simulate 20 million miles every single day [1]. Clearly, it's working for them given their scale of deployment right now.
[1] https://waymo.com/blog/2020/04/off-road-but-not-offline--sim...
Exactly. plus any delivery company/dashcam company can provide a bunch of data where ever there is any sizeable population.
About 8 years ago, that data would have been really valuable, but at best its nice to have.
the only thing that is valuable is the breadth of different cars, but even then its not that much of a differentiator.
And I don't like the idea of even more data being harvested and used.. I just find the dismissal.. odd.
No one is suggesting the latter.
Well, TBF, the tesla data was complete garbage with earlier vehicles. They had cheap and somewhat bad cameras in the earlier vehicles that was only somewhat recently updated. And even then, I don't think Tesla is at the end of their hardware journey. I think they don't think that either, which is why they've gone to a subscription only model for self driving vehicles.
Waymo, on the other hand, has gathered less data, but more high quality data. They do the expensive mapping of a city which is a big part of why their vehicles have early on been able to do some pretty impressive feats. The drawback is getting that high quality data takes a lot of time and resources.
I dunno about that. Tesla seems completely adrift, pretending to pivot with random forays into humanoid robotics or whatever, to the point that I wouldn't be surprised if they exited the consumer vehicle space altogether within the next decade. They have no answer for Chinese competitors.
As far as the self driving, they may be far off still, it’s hard for me to get a read on that and this vehicle is a bet that they will be able to achieve it - right down to the braille in the cabin, so maybe that’s why they still fail. The thing I will say is that despite the PR disaster that the CEO is, which gives us that feeling that the company has lost its mind, it seems they are still quietly doing some advanced engineering.
Is that the right kind of model for this particular application?
Problem 1: Cost and privacy constrain limit data collection.
Problem 2: It makes not much sense to collect and store data that you already have. Yet you don't know that when collecting if it is useful or not.
Problem 3: P2P in urban setting fails at edge cases which by definition are rare to collect.
All of these problems limit AV scaling.
Also, Uber’s data might be useful for eval, not training (e.g « here is how Waymo would behave vs human drivers therefore it is safer »)
Accidents and near-collisions are exactly the kind of scenarios perfect for simulation. You don't test them out in the real world and risk injuries/deaths. You need to have confidence they're handled before you deploy.
You can imagine improving i.e. a specialized math model (problem in, theorem out) with a normal LLM that knows lots of problems and theorems generally.
The world model is basically intended as a more true-to-life simulator.
Do you hear yourself?
https://waymo.com/waymo-driver/
That AI part is doing a lot of heavy lifting. They're using real data. We already know synthetic data is dangerous. Explains a lot of if you think it's more reliant on that than real data.
Uber did invest early in self driving back in 2015, but in 2018 there was a fatality which pretty much deleted their whole program. And looks like it's taken them way too long to try picking it back up.
Real-world data spoils faster than a gas station banana.
If your AV company is relying on data from six years ago, you're going to kill someone.
The original title says "self-driving" and that's much more clear.
I saw the title and thought it can't be AV, they must mean AI and made a typo.
This isn't a pivot, this is them trying to sheepishly reenter the race they were dramatically ejected from.
They run trucks for Fedex in Texas and wants to offer an "Uber Freight network"
There's nothing stopping the car makers from running their own taxi service and they already have networks of mechanics and cleaner as well as some level of storage. They'd need to scale up, but they don't need to start from zero.
Ubers success is in large part build on not having to own AND MANAGE their cars. With self-driving cars that advantage disappears, unless they're gaming that "drivers" will buy the cars and lease it to them.
Don’t they [1][2]?
[1] https://www.privacyinternational.org/examples/1929/tesla-lea...
[2] https://electrek.co/2020/10/24/tesla-collecting-insane-amoun...
I'm not sure about the privacy implications. You say "all its cars" but you actually mean "all its customers cars". The relationship between Uber and the cars/drivers is fairly different.
Self-driving is possible but it requires a massive sustained investment in custom hardware on the car, in real and simulation testing, in painstaking software developlment covering tens of thousands of scenarios, realtime remote control failsafes, fleet management capabilities in every city. Waymo is the only company that comes close to the right approach. All these other Elons, GM, Uber CEOs are just jangling shiny objects in front of investors. A moonshot on the financial model for what are otherwise mature stagnant businesses.
Can the drivers charge a monthly late for hosting the sensors?
Seems par for the course. Nintendo turned legions of Pokemon Go players into unpaid sensor grids for delivery robots.
He said he “didn’t care and besides what was he going to do about it anyway, it’s going to happen no matter what”
I asked if he had ever heard of collective bargaining or knew about unions and he said no.
I think we’re only about another generation before the only purpose for human labor is to train and check the outputs of a machine.
[1] Here's how you know:
“Our goal is not to make money out of this data,” Naga said. “We want to democratize it.”I think enough people haven’t been in a Waymo to realise that the technology is basically here, and that we’re like 10 to 20 years of doubling away from AVs doing tens of millions of trips a day in America. By the time anyone has invested in true mass production of AVs, we’ll already be so far down that path that the policy deck will be dealt.
So what are we walking into? Not 8-11 billion happy cows. A crisis. People deciding not to reproduce. The human population declining. The irony as we achieve a technical pinnacle while justifying our own extinction by choice. The great filter as it turns out is actually capitalism, a race to business efficiency against all else including the incentives of your very own species. This is the mind virus.
But that said, supposing we are looking at 60 years from now having a few billion fewer people on Earth, just by attrition (lack of replacement) that is not automatically bad. We could afford to shrink in population - if there’s a floor to that contraction. If indeed there are way too many people in a decade for the available human jobs, then it could be the equilibrium is just a lower population. Which could be temporary - who knows what the future could bring, such as possible space colonization, which may need more humans and also give people the hope that I think Gen Y and Z have lacked, which is one reason for their low repro rates.
The complete destruction of the human through exploitation and control, as seen in the article, is a major reason people are too unhappy to start families.
The worst part? Most people don't even know why, so there's never a general public reaction to fix it.
the only real argument for continued growth in to preserve the current structure of investment. that's your great filter, and it will result in economic collapse which isn't the same as extinction.
It’s here and it’s been here for decades - it’s just finally impossible to ignore or wave away
Gig workers are self-chattelizing because there is no floor to the depravity that society will accept, and an endless supply of people who will chattelize themselves for a moment of pleasure
Or perhaps they "chattelize" to survive?
There's not much pleasure to be had from gig work apart from the freedom to perhaps choose your own hours and perhaps be free of a human boss. Both of which are quite the opposite of chattelizing, in the short term.
The pleasure of being an Uber driver? Wouldn’t the better analogy be survival for most gig workers?
collective bargaining or unions do not prevent technological progress, but merely retard it in the hopes that their members can benefit at the cost of progress for everyone else. Look at dock workers and how they tried to prevent automation with unions.
Reminds me of when dockworkers resisted the shift to cargo containers. Those ports ultimately lost business in the end.
Uber torches 2026 AI budget on Claude Code in four months
It sounds like a terrible business plan.