The Waymo World Model
waymo.com
waymo.com
Google/Alphabet are so vertically integrated for AI when you think about it. Compare what they're doing - their own power generation , their own silicon, their own data centers, search Gmail YouTube Gemini workspace wallet, billions and billions of Android and Chromebook users, their ads everywhere, their browser everywhere, waymo, probably buy back Boston dynamics soon enough (they're recently partnered together), fusion research, drugs discovery.... and then look at ChatGPT's chatbot or grok's porn. Pales in comparison.
As soon as Waymo's massive robotaxi lead became undeniable, he pivoted to from robotaxis to humanoid robots.
The key question is whether general purpose robots can outcompete on sheer economies of scale alone.
Purpose built, that probably takes the form of a humanoid robot since all of tasks it needs to do were previously designed for humanoids.
Dusting with a single extensible and multiple degrees of freedom arm would be much more maneuverable than a human arm.
Loading and unloading washing machines or dryers or doign the same for dishes and cutlery in a dishwasher is not inherently designed for humans.
If anything, selling an integrated "housekeeping" system that fits into an existing laundry and combines features would be a much better approach.
For old/retrofit renovations it also makes sense, but otherwise, yes, a human-form robot makes sense.
The question is which is a better investment for any robot manufacturer in 2026?
I wonder how long they'll be closed for "modifications" and whether the Optimus Prime robot factories will go into production before the "Trump Kennedy Center" is reopened after its "renovations".
Using vision only is so ignorant of what driving is all about: sound, vibration, vision, heat, cold...these are all clues on road condition. If the car isn't feeling all these things as part of the model, you're handicapping it. In a brilliant way Lidar is the missing piece of information a car needs without relying on multiple sensors, it's probably superior to what a human can do, where as vision only is clearly inferior.
7 cameras x 36fps x 5Mpx x 30s
48kHz audio
Nav maps and route for next few miles
100Hz kinematics (speed, IMU, odometry, etc)
Also, integration effort went down but it never disappeared. Meanwhile, opportunity cost skyrocketed when vision started working. Which layers would you carve resources away from to make room? How far back would you be willing to send the training + validation schedule to accommodate the change? If you saw your vision-only stack take off and blow past human performance on the march of 9s, would you land the plane just because red paint became available and you wanted to paint it red?
I wouldn't completely discount ego either, but IMO there's more ego in the "LIDAR is necessary" case than the "LIDAR isn't necessary" at this point. FWIW, I used to be an outspoken LIDAR-head before 2021 when monocular depth estimation became a solved problem. It was funny watching everyone around me convert in the opposite direction at around the same time, probably driven by politics. I get it, I hate Elon's politics too, I just try very hard to keep his shitty behavior from influencing my opinions on machine learning.
It's still rather weak and true monocular depth estimation really wasn't spectacularly anything in 2021. It's fundamentally ill posed and any priors you use to get around that will come to bite you in the long tail of things some driver will encounter on the road.
The way it got good is by using camera overlap in space and over time while in motion to figure out metric depth over the entire image. Which is, humorously enough, sensor fusion.
I do some tangent work from this field for applications in robotics, and I would consider (metric) depth estimation (and 3D reconstruction) starting to be solved only by 2025 thanks to a few select labs.
Car vision has some domain specificity (high similarity images from adjacent timestamps, relatively simpler priors, etc) that helps, indeed.
Source: not a computer vision engineer, but a childhood consumer of looney toons cartoons.
None of these technologies can ever be 100%, so we’re basically accepting a level of needless death.
Musk has even shrugged off FSD related deaths as, “progress”.
FSD: 2 deaths in 7 billion miles
Looks like FSD saves lives by a margin so fat it can probably survive most statistical games.
Your link agrees with me:
> 2 fatalities involving the use of FSD
No one wants these crappy cars anymore.
https://en.wikipedia.org/wiki/List_of_Tesla_Autopilot_crashe...
Your link agrees with me:
> two that NHTSA's Office of Defect Investigations determined as happening during the engagement of Full Self-Driving (FSD) after 2022.
"MacOS Tahoe has these cool features". "Yea but what about this wikipedia article on System 1. Look it has these issues."
That's how you come across
There are two deaths associated with FSD.
[*] Failing to solve the impossible situation FSD dropped them into, that is.
https://www.nhtsa.gov/laws-regulations/standing-general-orde...
If there's gamesmanship going on, I'd expect the antifan site linked below to have different numbers, but it agrees with the 2 deaths figure for FSD.
No customer would turn on FSD on an icy road, or on country lanes in the UK which are one lane but run in both directions; it's much harder to have a passenger fatality in stop-start traffic jams in downtown US cities.
Even if those numbers are genuine (2 vs 70) I wouldn't consider it apples-for-apples.
Public information campaigns and proper policing have a role to play in car safety, if that's the stated goal we don't necessarily need to sink billions into researching self driving
https://www.yellowscan.com/knowledge/how-weather-really-affe...
Seeing how its by a lidar vendor, I don't think they're biased against it. It seems Lidar is not a panacea - it struggles with heavy rain, snow, much more than cameras do and is affected by cold weather or any contamination on the sensor.
So lidar will only get you so far. I'm far more interested in mmwave radar, which while much worse in spatial resolution, isn't affected by light conditions, weather, can directly measure stuff on the thing its illuminating, like material properties, the speed its moving, the thickness.
Fun fact: mmWave based presence sensors can measure your hearbeat, as the micro-movements show up as a frequency component. So I'd guess it would have a very good chance to detect a human.
I'm pretty sure even with much more rudimentary processing, it'll be able to tell if its looking at a living being.
By the way: what happened to the idea that self-driving cars will be able to talk to each other and combine each other's sensor data, so if there are multiple ones looking at the same spot, you'd get a much improved chance of not making a mistake.
Um, yes they did.
No idea if it had any relation to Tesla though.
0: https://techcrunch.com/2019/04/22/anyone-relying-on-lidar-is...
1: https://static.mobileye.com/website/corporate/media/radar-li...
2: https://www.luminartech.com/updates/luminar-accelerates-comm...
3: https://www.youtube.com/watch?v=Vvg9heQObyQ&t=48s
4: https://ir.innoviz.tech/news-events/press-releases/detail/13...
Then that guy got decapitated when his Model S drove under a semi-truck that was crossing the highway and Mobileye terminated the contract. Weirdly, the same fatal edge case occurred 2 more times at least on Tesla's newer hardware.
https://en.wikipedia.org/wiki/List_of_Tesla_Autopilot_crashe...
Having a self-driving solution that can be totally turned off with a speck of mud, heavy rain, morning dew, bright sunlight at dawn and dusk.. you can't engineer your way out of sensor-blindness.
I don't want a solution that is available to use 98% of the time, I want a solution that is always-available and can't be blinded by a bad lighting condition.
I think he did it because his solution always used the crutch of "FSD Not Available, Right hand Camera is Blocked" messaging and "Driver Supervision" as the backstop to any failure anywhere in the stack. Waymo had no choice but to solve the expensive problem of "Always Available and Safe" and work backwards on price.
And it's still not clear whether they are using a fallback driving stack for a situation where one of non-essential (i.e. non-camera (1)) sensors is degraded. I haven't seen Waymo clearly stating capabilities of their self-driving stack in this regard. On the other hand, there are such things as washer fluid and high dynamic range cameras.
(1) You can't drive in a city if you can't see the light emitted by traffic lights, which neither lidar nor radar can do.
Lidar also gives you the ability to see through fog and as it scans, see the depth needed to nearly always understand what object is in front of them.
My Model 3 shows "degraded" or "unavailable" about 2% of the time i'm driving around populated areas. Zero chance it will ever be truly FSD capable, no matter the software improvements. It'll still be unavailable because the cameras are blinded/blocked/unable to process the scene because it can't see the scene.
While you're right, washer fluid works usually on the windshield, it doesn't on the side cameras, and yea hdr could improve things, it won't improve depth perception, and this will never be installed on my model 3..
Lidar contributes the data most needed to handle the millions of edge cases that exist. With both camera and lidar contributing the data they are both the best at collecting, the risk of the very worst type of accidents is greatly reduced.
I don't see these stats https://waymo.com/safety/impact/ happening for tesla anytime soon.
but with occasional remote guidance (Waymo doesn't seem to disclose statistics of that). In some cases remote guidance includes placing waypoints[1].
> Lidar also gives you the ability to see through fog and as it scans
Nah. Lidar isn't much better in fog than cameras. If I'm not mistaken, fog, rain, smoke, snow scatter IR light approximately the same as visible light. The lidar beam needs to travel twice the distance and its power is limited by eye-safety concerns.
> FSD on my model 3 to be even nearly perfect all the time
It doesn't need to be perfect. It needs to not hit things, cars and pedestrians too hard and too often, while mostly obeying traffic rules. Waymo has quite a few complains about their cars' behavior[2], but they manage just fine.
[1] third video in https://waymo.com/blog/2024/05/fleet-response
All you really need is "drive slower if you can't see (because rain, fog, or degraded cameras), or you're in an area where children might run out into the road"
And I agree, it is. Clearly it is theoretically possible without.
But when you can't walk at all, a crutch might be just what you need to get going before you can do it without the crutch!
That’s true now, but when they first debuted they would have doubled the cost of the car.
Of course, things have changed.
Had Tesla gone all-in on Lidar, they could have turned the technology into a commodity, they are a trillion dollar company producing a million cars a year. Lidar is already present on cheap robot vacuum cleaners, and we have time-of-flight cameras in smartphones, I don't believe it would have been a problem to equip $50k cars with Lidar.
This is huge though.
People aren't setting them on fire during protests, and if an FSD Tesla plows into a farmers market, it might not even make the news.
People hate tech so much that self-driving companies with easy-to-spot cars have had to shut down after just a few mistakes.
Disguising Teslas as plain old regular human-driven cars is a great idea and I wouldn't be surprised if they win the market because of this. Even if they suck at driving.
https://www.forbes.com/sites/conormurray/2025/05/01/tesla-pr...
Additionally, Flash required android phones with 256MB ram as a minimum (which would have precluded two of the three shipped iPhone models at the time) and at least initially only supported software video decoding. Because of the difference in screen dimensions, resolutions and interaction models (plus the issues with embedding due to RAM limitations), the website was still basically broken whether your mobile phone had Flash or not.
My understanding (based on the timing) was always that when Adobe was finally ready to push its partners to bundle mobile Flash, Apple looked at it and decided against it. Adobe made public statements against their partner and so Jobs did so in kind.
I will never trust 2d camera-only, it can be covered or blocked physically and when it happens FSD fails.
As cheap as LIDAR has gotten, adding it to every new tesla seems to be the best way out of this idiotic position. Sadly I think Elon got bored with cars and moved on.
The issue with lidar is that many of the difficult edge-cases of FSD are all visible-light vision problems. Lidar might be able to tell you there's a car up front, but it can't tell you that the car has it's hazard lights on and a flat tire. Lidar might see a human shaped thing in the road, but it cannot tell whether it's a mannequin leaning against a bin or a human about to cross the road.
Lidar gets you most of the way there when it comes to spatial awareness on the road, but you need cameras for most of the edge-cases because cameras provide the color data needed to understand the world.
You could never have FSD with just lidar, but you could have FSD with just cameras if you can overcome all of the hardware and software challenges with accurate 3D perception.
Given Lidar adds cost and complexity, and most edge cases in FSD are camera problems, I think camera-only probably helps to force engineers to focus their efforts in the right place rather than hitting bottlenecks from over depending on Lidar data. This isn't an argument for camera-only FSD, but from Tesla's perspective it does down costs and allows them to continue to produce appealing cars – which is obviously important if you're coming at FSD from the perspective of an auto marker trying to sell cars.
Finally, adding lidar as a redundancy once you've "solved" FSD with cameras isn't impossible. I personally suspect Tesla will eventually do this with their robotaxis.
That said, I have no real experience with self-driving cars. I've only worked on vision problems and while lidar is great if you need to measure distances and not hit things, it's the wrong tool if you need to comprehend the world around you.
But the Tesla engineers are "in the right place rather than hitting bottlenecks from over depending on Lidar data"? What?
The real question is whether doing so is smart or dumb. Is Tesla hiding big show-stopper problems that will prevent them from scaling without a safety driver? Or are the big safety problems solved and they are just finishing the Robotaxi assembly line that will crank out more vertically-integrated purpose-designed cars than Waymo's entire fleet every day before lunch?
What good is a huge fleet of Robotaxis if no one will trust them? I won't ever set foot in a Robotaxi, as long as Elon is involved.
First pedestrian struck. That's crazy.
Tesla just disengages fsd anytime a sensor is slightly blocked/covered/blinded.. waymo out here doing fsd 100% of the time and basically never hurts anyone.
I don't get the tesla/elon love here, i like my model 3 but it's never going to get real fsd, and that sucks, elon also lies about the roadmap, timing, etc. I bet the roadster is canceled now. Why do people like inferior sensors and autistic hitler?
I’m sure latency and connectivity is too much of an risk to do it any other way.
The only Waymos driven by a human are the ones with human drivers physically in the car
I don't think Tesla is that far behind Waymo though given Waymo has had a significant head start, the fact Waymo has always been a taxi-first product, and given they're using significantly more expensive tech than Tesla is.
Additionally, it's not like this is a lidar vs cameras debate. Waymo also uses and needs cameras for FSD for the reasons I mentioned, but they supplement their robotaxis with lidar for accuracy and redundancy.
My guess is that Tesla will experiment with lidar on their robotaxis this year because design decisions should differ from those of a consumer automobile. But I could be wrong because if Tesla wants FSD to work well on visually appealing and affordable consumer vehicles then they'll probably have to solve some of the additional challenges with with a camera-only FSD system. I think it will depend on how much Elon decides Tesla needs to pivot into robotaxis.
Either way, what is undebatable is that you can't drive with lidar only. If the weather is so bad that cameras are useless then Waymos are also useless.
I understand that small lens sizes mean that falling droplets can obstruct the view behind the droplet, while larger lens sizes can more easily see beyond the droplet.
I seldom see discussion of the exact failure modes for specific weather conditions. Even if larger lenses are selected the light source should use similar lens dimensions. Independent modulation of multiple light sources could also dramatically increase the gained information from each single LiDAR sensor.
Do self-driving camera systems (conventional and LiDAR) use variable or fixed tilt lenses? Normal camera systems have the focal plane perpendicular to the viewing direction, but for roads it might be more interesting to have a large swath of the horizontal road in focus. At least having 1 front facing camera with a horizontal road in focus may prove highly beneficial.
To a certain extend an FSD system predicts the best course of action. When different courses of action have similar logits of expected fitness for the next best course of action, we can speak of doubt. With RMAD we can figure out which features or what facets of input or which part of the view is causing the doubt.
A camera has motion blur (unless you can strobe the illumination source, but in daytime the sun is very hard to outshine), it would seem like an interesting experiment to:
1. identify in real time which doubts have the most significant influence on the determination of best course of action
2. have a camera that can track an object to eliminate motion blur but still enjoy optimal lighting (under the sun, or at night), just like our eyes can rotate
3. rerun the best course of action prediction and feed back this information to the company, so it can figure out the cost-benefit of adding a free tracking camera dedicated to eliminating doubts caused by motion blur.
I thought it was the Nazi salutes on stage and backing neo-nazi groups everywhere around the world, but you know, I guess the lidar thing too.
It sounds like they removed Lidar due to supplier issues and availability, not because they're trying to build self-driving cars and have determined they don't need it anymore.
I get it in the context of driverless but find it nothing but annoying as a driver.
They are just aids that ease fatigue on long trips.
It's more so the result of being awake, doing effectively nothing, for a long time. Lane Keep assistance is a useless technology for 99% of the population and the 1% who need it, likely shouldn't be driving a car anyways.
The more we "aid" fatigue, the longer drivers will attempt to drive. This cannot be a good outcome. The worst driving occurs when one is practically half asleep.
If you’ve ever driven a 1970s truck you’ll know that continually correcting the steering will wear you out after just a couple of hours. Modern rack and pinion steering is a lot more comfortable, and lane keep is a further comfort improvement.
Google's been thinking about world models since at least 2018: https://arxiv.org/abs/1803.10122
Erm, a dishwasher, washing machine, automated vacuum can be considered robots. Im confused as to this obsession of the term - there are many robots that already exist. Robotics have been involved in the production of cars for decades.
......
Dictionary def: "a machine controlled by a computer that is used to perform jobs automatically."
Maybe we need to nitpick about what a job is exactly? Or we could agree to call Waymos (semi)autonomous robots?
But in my mind a waymo was always a "car with sensors", but more recently (especially having recently used them a bunch in California recently) I've come to think of them truly as robots.
Even if that definition were universally agreed on l upon though, that's not really enough to understand what the parent comment was saying. Being a robot "in the same way" as something else is even less objective. Humans are humans, but they're also mammals; is a human a mammal "in the same way" as a mouse? Most humans probably have a very different view of the world than most mice, and the parent comment was specifically addressing the question of whether it makes sense for an autonomous car to model the world the same way as other robots or not. I don't see how you can dismiss this as "irrelevant" because both humans and mice are mammals (or even animals; there's no shortage of classifications out there) unless you're completely having a different conversation than the person you responded to. You're not necessarily wrong because of that, but you're making a pretty significant misjudgment if you think that's helpful to them or to anyone else involved in the ongoing conversation.
Boston Robotics is working on a smaller robot that can kill you.
Anduril is working on even smaller robots that can kill you.
The future sucks.
[1] https://www.wsj.com/tech/personal-tech/i-tried-the-robot-tha...
[2] https://futurism.com/advanced-transport/waymos-controlled-wo...
If that doesn't make it obvious what they can and cannot do then I can't respect the tranche of "hackers" who blindly cheer on this unchecked corporate dystopian nightmare.
Solving the technical challenges and using that solution profitably are two completely different things.
The key metric is more unusual situations. That scales with miles driven, not gigabytes. With onboard inference the car simply logs anything 'unusual' (low confidence) to selectively upload those needle-in-a-haystack rare events.
But Codex/5.2 was substantially more effective than Claude at debugging complex C++ bugs until around Fall, when I was writing a lot more code.
I find Gemini 3 useless. It has regressed on hallucinations from Gemini 2.5, to the point where its output is no better than a random token stream despite all its benchmark outperformance. I would use Gemini 2.5 to help write papers and all, can't see to use Gemini 3 for anything. Gemini CLI also is very non-compliant and crazy.
I don't think Google is targeting developers with their AI, they are targeting their product's users.
[1]: https://research.google/blog/towards-a-conversational-agent-...
In many ways, turning tech into products that are useful, good, and don't make life hell is a more interesting issue of our times than the core research itself. We probably want to avoid the valuing capturing platform problem, as otherwise we'll end up seeing governments using ham fisted tools to punish winners in ways that aren't helpful either
It’s kind of crazy that they have been slow to create real products and competitive large scale models from their research.
But they are in full gear now that there is real competition, and it’ll be cool to see what they release over the next few years.
You're making an interesting point that I somewhat agree with from the perspective of someone was...clearly a little more feral than his surroundings in Google, and wildly succeeded and ultimately quietly failed because of it.
The important bit is "great man" theory doesn't solve lack of dynamism. It usually makes things worse. The people you read about in newspapers are pretty much as smart as you, for better or worse.
I actually disagreed with the Sergey thing along the same lines, it was being used as a parable for why it was okay to do ~nothing in year 3 and continue avoiding what we were supposed to ship in year 1, because only VPs outside my org and the design section in my org would care.
Not sure if all that rhymes or will make any sense to you at all. But I deeply respect the point you are communicating, and also mean to communicate that there's another just as strong lesson: one person isn't bright enough to pull that off, and the important bit there isn't "oh, he isn't special", it's that it makes you even more careful building organizations that maintain dynamism and creativity.
E.g. Steve Jobs was absolutely fundamental to the turn around of Apple. Will Brin have this level of incremental impact on the Goog/Alphabet of today? Nah.
But if you look at Google, there isn't one key product. There are a whole pile of products that are best in class. Search (cringe, I know it's popular here to say Google search sucks and perhaps it does, but what search engine is far better?), YouTube, Maps, Android, Waymo, GMail, Deep Mind, the cloud infrastructure, translate, lens (OCR) and probably a lot of others I've forgotten. Don't forget Sheets and Docs, which while they have been replicated by Microsoft and others now were first done by Google. Some of them, like Maps, seem to have swapped entire teams - yet continued to be best in class. Predicting Google won't be at the forefront on the next advance seems perilous.
Maybe these products have key people as you call them, but the magic in Alphabet doesn't seem to be them. The magic seems to be Alphabet has some way to create / acquire these keep people. Or perhaps Alphabet just knows how to create top engineering teams that keep rolling along, even when the team members are replaced.
Apple produced one key person, Jobs. Alphabet seems to be a factory creating lots of key people moving products along. But as Google even manages to replace these key people (as they did for Maps) and still keep the product moving, I'm not sure they are the key to Googles success.
Since you ask, this surely has to be altpower.app!
The worst part was figuring what happened way too late. People were having trying to go for promo for a project that didn't launch. Many people got angry, some left, the product felt stale and leadership&management lost trust.
(cheers, don't read too much signal into my thoughts, it's more negative than I'd intend. Just was aware it was someone going off PR, and doing hero worship that I myself used to do, and was disabused over 7 years there, and would like other people outside to disabuse themselves of. It's a place, not the place)
Google Reader is a simple example: Googl had by far the most popular RSS reader, and they just threw it away. A single intern could have kept the whole thing running, and Google has literal billions, but they couldn't see the value in it.
I mean, it's not like being able to see what a good portion of America is reading every day could have any value for an AI company, right?
Google has always been terrible about turning tech into (viable, maintained) products.
See also: any programming thread and Rust.
Therefore we now have “Vinkel’s Law”
Reader had to be killed because it [was seen as] a suboptimal ad monetization engine. Page views were superior.
Was Google going to support minimizing ads in any way?
It was Google clearly seeing the product’s value, and killing it because that value was detrimental to their ads business.
https://www.wsj.com/finance/jeffrey-epstein-advised-sergey-b...
On a similar topic, it is worth mentioning the entrepreneurs that are forced into sex (or let’s say, very pushed) by VCs.
For those who feel safe or taking it as a joke, this affects women AND men.
Some people are going to be disappointed about their heroes.
Barely any of these jokers are clean. Makes MZ look seemingly normal in comparison.
Wait for the second set of files...
"...One of Mr. Epstein’s former boat captains told The New York Times earlier this year that he had seen Mr. Brin on the island more than once..."
https://dnyuz.com/2026/01/31/powerful-men-who-turn-up-in-the...
I always thought they deliberately tried to contain the genie in the bottle as long as they could
I think they were worried that releasing a product like ChatGPT only had downside risks for them, because it might mess up their money printing operation over in advertising by doing slurs and swears. Those sweet summer children: little did they know they could run an operation with a seig-heiling CEO who uses LLMs to manufacture and distribute CSAM worldwide, and it wouldn't make above-the-fold news.
[1] https://en.wikipedia.org/wiki/LaMDA#Sentience_claims
[2] https://research.google/blog/lamda-towards-safe-grounded-and...
Time will tell if LLM training becomes a race to the bottom or the release of the "open source" ones proves to be a spoiler. From the outside looking while ChatGPT has brand recognition for the average person who could not tell the difference between any two LLMs google offering Gemini in android phones could perhaps supplant them.
Not really. If Google released all of this first instead of companies that have never made a profit and perhaps never will, the case law would simply be the copyright holders suing them for infringement and winning.
It’s not that crazy. Sometimes the rational move is to wait for a market to fully materialize before going after it. This isn’t a Xerox PARC situation, nor really the innovator’s dilemma, it’s about timing: turning research into profits when market conditions finally make it viable. Even mammoths like Google are limited in their ability to create entirely new markets.
It'll be interesting to see which pays off and which becomes Quibi
They should be bought by a rocket company. Then they would stand a chance.
I know it’s gross, but I would not discount this. Remember why Blu-ray won over HDDVD? I know it won for many other technical reasons, but I think there are a few historical examples of sexual content being a big competitive advantage.
>I've never really thought of Waymo as a robot in the same way as e.g. a Boston Dynamics humanoid, but of course it is a robot of sorts.
IMO the presence of safety chase vehicles is just a sensible "as low as reasonably achievable" measure during the early rollout. I'm not sure that can (fairly) be used as a point against them.
I'm comfortably with Tesla sparing no expense for safety, since I think we all (including Tesla) understand that this isn't the ultimate implementation. In fact, I think it would be a scandal if Tesla failed to do exactly that.
Damned if you do and damned if you don't, apparently.
Only if you're comparing them to another company, which you seem to be. So yes, yes it can.
Seriously, the amount of sheer cope here is insane. Waymo is doing the thing. Tesla is not. If Tesla were capable of doing it, they would be. But they're not.
It really is as simple as that and no amount of random facts you may bring up will change the reality. Waymo is doing the thing.
This worldview is overly simplistic.
Waymo has (very shrewdly, for prospective investors at least) executed a strategy that most quickly scales to 0.1% of the population. Unfortunately it doesn't scale further. The cars are too costly and the mapping is too costly. There is no workable plan for significant scale from Waymo.
Tesla is executing the strategy that most quickly scales to 100% of the population.
So, uh… where is this “scale” then? This “strategy” has been bandied about for better part of a decade. Why are they still in a tiny geofence in Austin with chase cars?
Waymo is doing it right now. Half a million rides every week, expansion to a dozen new cities. Tesla does a few hundred in a tiny area.
Scale is assessed by looking at concrete numbers, not by “strategies” that haven’t materialized for a decade.
Data suggests that they’re already available to ~2% of the US population.
So "maybe cars are a bit of robots too" is more like 30-50 years behind the time.
I view Tesla also more as a robot company than anything else.
Tesla claimed that all their "real world" recording would give them a moat on FSD.
Waymo is showing that a) you need to be able to incorporate stuff that isn't "real" when training, and b) you get a lot more information from alternate sensors to visible spectrum only.
If the former then it’s relevant to the broader discourse on LLM generality. If the latter, then it seems less relevant to chatbots and business agents.
Edit to add: this is not part of the model, it’s in a separate pillar (Simulator vs Driver). More at https://waymo.com/blog/2025/12/demonstrably-safe-ai-for-auto....
The apparent applicability to Waymo is incidental, more likely because a few millions+ were spent on Genie and they have to do something with it. DeepMind started to train "world models" because that's the current overhyped buzzword in the industry. First it was "natural language understanding" and "question answering" back in the days of old BERT, then it was "agentic", then "reasoning", now it's "world models", next years it's going to be "emotions" or "social intelligence" or some other anthropomorphic, over-drawn neologism. If you follow a few AI accounts on social media you really can't miss when those things suddenly start trending, then pretty much die out and only a few stragglers still try to publish papers on them because they failed to get the memo that we're now all running behind the Next Big Thing™.
Edit:
This just in:
https://news.ycombinator.com/item?id=46870514#46929215
The Next Big Thing™ is going to be "context learning", at least if Tencent have their way. And why do we need that?
>> Current language models do not handle context this way. They rely primarily on parametric knowledge—information compressed into their weights during massive pre-training runs. At inference time, they function largely by recalling this static, internal memory, rather than actively learning from new information provided in the moment.
>> This creates a structural mismatch. We have optimized models to excel at reasoning over what they already know yet users need them to solve tasks that depend on messy, constantly evolving context. We built models that rely on what they know from the past, but we need context learners that rely on what they can absorb from the environment in the moment.
Yep. Reasoning is so 2025.
Why doesn't this site have a block user button?
Subtle brag that Waymo could drive in camera-only mode if they chose to. They've stated as much previously, but that doesn't seem widely known.
(edit - I'm referring to deployed Tesla vehicles, I don't know what their research fleet comprises, but other commenters explain that this fleet does collect LIDAR)
https://youtu.be/LFh9GAzHg1c?t=872
They've also built it into a full neural simulator.
https://youtu.be/LFh9GAzHg1c?t=1063
I think what we are seeing is that they both converged on the correct approach, one of them decided to talk about it, and it triggered disclosure all around since nobody wants to be seen as lagging.
So...nowhere?
Why should you be able to do that exactly? Human vision is frequently tricked by it's lack of depth data.
Humans do this, just in the sense of depth perception with both eyes.
More subtly, a lot of depth information comes from how big we expect things to be, since everyday life is full of things we intuitively know the sizes of, frames of reference in the form of people, vehicles, furniture, etc . This is why the forced perspective of theme park castles is so effective— our brains want to see those upper windows as full sized, so we see the thing as 2-3x bigger than it actually is. And in the other direction, a lot of buildings in Las Vegas are further away than they look because hotels like the Bellagio have large black boxes on them that group a 2x2 block of the actual room windows.
It's possible they get headaches from the focal length issues but that's different.
Also subtle head and eye movements, which is something a lot of people like to ignore when discussing camera-based autonomy. Your eyes are always moving around which changes the perspective and gives a much better view of depth as we observe parallax effects. If you need a better view in a given direction you can turn or move your head. Fixed cameras mounted to a car's windshield can't do either of those things, so you need many more of them at higher resolutions to even come close to the amount of data the human eye can gather.
1. Crane my neck forward, see if I can see around it.
2. Inch forward a bit more, keep craning my neck.
3. Recognize, no, I'm still occluded.
4. Count on the heuristic analysis of the light filtering through the bush and determine if the change in light is likely movement associated with an oncoming car.
My Tesla's perpendicular camera is... mounted behind my head on the B-pillar... fixed... and sure as hell can't read the tea leaves, so to speak, to determine if that slight shadow change increases the likelihood that a car is about to hit us.
I honestly don't trust it to pull out of the alley. I don't know how I can. I'd basically have to be nose-into-right-lane for it to be far enough ahead to see conclusively.
Waymo can beam the LIDAR above and around the bush, owing to its height and the distance it can receive from, and its camera coverage to the perpendicular is far better. Vision only misses so many weird edge cases, and I hate that Elon just keeps saying "well, humans have only TWO cameras and THEY drive fine every day! h'yuck!"
And, importantly, the fender-mount LIDARs. It doesn't just have the one on the roof, it has one on each corner too.
I first took a Waymo as a curiosity on a recent SF trip, just a few blocks from my hotel east on Lombard to Hyde and over to the Buena Vista to try it out, and I was immediately impressed when we pulled up the hill to Larkin and it saw a pedestrian that was out of view behind a building from my perspective. Those real-time displays went a long way to allowing me to quickly trust that the vehicle's systems were aware of what's going on around it and the relevant traffic signals. Plenty of sensors plus a detailed map of a specific environment work well.
Compare that to my Ioniq5 which combines one camera with a radar and a few ultrasonic sensors and thinks a semi truck is a series of cars constantly merging in to each other. I trust it to hold a lane on the highway and not much else, which is basically what they sell it as being able to do. I haven't seen anything that would make me trust a Tesla any further than my own car and yet they sell it as if it is on the verge of being able to drive you anywhere you want on its own.
There have been a few attempts at solving this, but I assume that for some optical reason actual lenses need to be adjusted and it can't just be a change in the image? Meta had "Varifocal HMDs" being shown off for a bit, which I think literally moved the screen back and forth. There were a couple of "Multifocal" attempts with multiple stacked displays, but that seemed crazy. Computer Generated Holography sounded very promising, but I don't know if a good one has ever been built. A startup called Creal claimed to be able to use "digital light fields", which basically project stuff right onto the retina, which sounds kinda hogwashy to me but maybe it works?
Here is a study on how these effects rank when it’s comes to (hand) reaching tasks in VR: https://pubmed.ncbi.nlm.nih.gov/29293512/
Humans do this with vibes and instincts, not just depth perception. When I can't see the lines on the road because there's too much slow, I can still interpret where they would be based on my familiarity with the roads and my implicit knowledge of how roads work, e.g. We do similar things for heavy rain or fog, although, sometimes those situations truly necessitate pulling over or slowing down and turning on your 4s - lidar might genuinely given an advantage there.
The next generation of that, the ATX, is the one they have said would be half that cost. According to regulator filings in China BYD will be using this on entry level $10k cars.
Hesai got the price down for their new generation by several optimizations. They are using their own designs for lasers, receivers, and driver chips which reduced component counts and material costs. They have stepped up production to 1.5 million units a year giving them mass production efficiencies.
Tesla told us their strategy was vertical integration and scale to drive down all input costs in manufacturing these vehicles...
...oh, except lidar, that's going to be expensive forever, for some reason?
> Then, in December 2016, Waymo received evidence suggesting that Otto and Uber were actually using Waymo’s trade secrets and patented LiDAR designs. On December 13, Waymo received an email from one of its LiDAR-component vendors. The email, which a Waymo employee was copied on, was titled OTTO FILES and its recipients included an email alias indicating that the thread was a discussion among members of the vendor’s “Uber” team. Attached to the email was a machine drawing of what purported to be an Otto circuit board (the “Replicated Board”) that bore a striking resemblance to – and shared several unique characteristics with – Waymo’s highly confidential current-generation LiDAR circuit board, the design of which had been downloaded by Mr. Levandowski before his resignation.
The presiding judge, Alsup, said, "this is the biggest trade secret crime I have ever seen. This was not small. This was massive in scale."
(Pronto connection: Levandowski got pardoned by Trump and is CEO of Pronto autonomous vehicles.)
https://arstechnica.com/tech-policy/2017/02/waymo-googles-se...
That was 2 generations of hardware ago (4th gen Chrysler Pacificas). They are about to introduce 6th gen hardware. It's a safe bet that it's much cheaper now, given how mass produced LiDARs cost ~$200.
And I'll add that it in practice it is not even that much unless you're doing some serious training, like a professional athlete. For most tasks, the accurate depth perception from this fades around the length of the arms.
All the shit out there in the world is another story.
Write a sonnet about Elon musk.
If you increase the distance of stereo cameras you probably can increase depth perception.
But a lidar or radar sensor is just sensing distance.
It's not all sunshine and roses to be honest - it was one of the weakest links in the perception system. The video had to run at way higher resolutions than it would otherwise and it was incredibly sensitive to calibration accuracy.
We do a lot more internal image processing. For example, relative motion as seen by either eye helps improve accuracy by a whole lot, in the "medium" distance range.
How do you know the generated outputs are correct? Especially for unusual circumstances?
Say the scenario is a patch of road is densely covered with 5 mm ball bearings. I'm sure the model will happily spit out numbers, but are they reasonable? How do we know they are reasonable? Even if the prediction is ok, how do we fundamentally know that the prediction for 4 mm ball bearings won't be completely wrong?
There seems to be a lot of critical information missing.
I mean would I like a in-depth tour of this? Yes.
But it's a marketing blog article, what do you expect?
And? The entire hallucination problem with text generators is "plausible sounding yet incorrect", so how does a human eyeballing it help at all?
You can also probably still use it for some kinds of evaluation as well since you can detect if two point clouds intersect presumably.
In much a similar way that LLMs are not perfect at translation but are widely used anyway for NMT.
I can spot Halluzination in LLM too
A sims style game with this technology will be pretty nice!
In other words it is a gradient from "my current prediction" to "best prediction given my imperfect knowledge" to "best prediction with perfect knowledge", and you can improve the outcome by shrinking the gap between 1&2 or shrinking the gap between 2&3 (or both)
For example, we know from experience that Waymo is currently good enough to drive in San Francisco. We don’t yet trust it in more complex environments like dense European cities or Southeast Asian “hell roads.” Running the stack against world models can give a big head start in understanding what works, and which situations are harder, without putting any humans in harm’s way.
We don’t need perfect accuracy from the world model to get real value. And, as usual, the more we use and validate these models, the more we can improve them; creating a virtuous cycle.
You can get 80% of the way to "perfect" with 20% of the effort.
Think of it more like unit tests. "In this synthetic scenario does the car stop as expected, does it continue as expected." You might hit some false negatives but there isn't a downside to that.
If it turns out your model has a blind spot for albino cows in a snow storm eating marshmallows, you might be able to catch that synthetically and spend some extra effort to prevent it.
do that for enough different scenarios, and if the model is consistently accurate across every scenario you validate, then you can start believing that it will also be accurate for the scenarios you haven't (and can't) validate.
https://www.yahoo.com/news/articles/waymo-paralyzed-parade-b...
In the video from the parade... there's just... people in the road. Like, a lot of small children and actual people on this tiny, super narrow bridge. I think that erring on the side of "don't think you can make it but accidentally drag a small child instead" is probably the right call, though admittedly, these cases are a bit wonky.
Which isn't really a scalable solution. In my city the majority of streetlights switch to blinking yellow at night, with priority/yield signs instead. I can't imagine a human having to approve 10 of these on any route.
You know the outputs are correct because the models have many billions of parameters and were trained on many years of video on many hectares of server farms. Of course they'll generate correct outputs!
I mean that's literally the justification. There aren't even any benchmarks that you can beat with video generation, not even any bollocks ones like for LLMs.
I think you'd be surprised. Look at the difference in cost per passenger mile.
I guess you're comparing the total cost of trains vs a subset of costs of cars, as is usual. Road use and pollution are free externalities after all.
As soon as a mode of transport actually has to compete in a market for scarce & valuable land to operate on, trains and other forms of transit (publicly or privately owned) win every time.
Where trains work they are great. Where they don't, driverless electric cars seem like a great option.
https://csh.ac.at/news/over-half-of-global-commutes-are-by-c...
Is there a magic road wand?
Roads are subsidized, free parking (and generally a lot of paid parking) is subsidized, and the sprawl encouraged by car dependence combined with the resulting infrastructure costs has and will continue to bankrupt cities.
I don't think we should "just only have trains", but the current US transit landscape is absurdly stupid and inefficient.
Source? The biggest source of environmental issues from EVs, tire wear from a heavier vehicle, absolutely applies to AVs. VC subsidizing low prices only to hike them later isn't exactly "without subsidy" - we pay for it either way
sure, a private vehicle is better for me, but a train is better for the world
Don't they have those somewhere in South America?
So many people advocate for public transit, but are unwilling to deal with the current market tradeoffs and decisions people are making on the ground. As long as that keeps happening, expect modes of transit -- like Waymo -- that deliver the level of service that they promise to keep exceeding expectations.
I've spent my entire adult life advocating for transportation alternatives, and at every turn in America, the vast majority of other transit advocates just expect people to be okay with anti-social behavior going completely unenforced, and expecting "good citizens" to keep paying when the expected value for any rational person is to engage in freeloading. Then they point to "enforcing the fare box" as a tradeoff between money to collect vs cost of enforcement, when the actually tradeoff is the signalling to every anti-social actor in the system that they can do whatever they want without any consequences.
I currently only see a future in bike-share, because it's the only system that actually delivers on what it promises.
This isn't just happening in America. Train systems are in rough shape in the UK and Germany too.
Ebike shares are a much more sustainable system with a much lower cost, and achieve about 90% of the level of service in temperate regions of the country. Even the ski-lift guy in this thread has a much more reasonable approach to public transit, because they actually have extremely low cost for the level of service they provide. Their only real shortcoming is they they don't handle peak demand well, and are not flexible enough to handle their own success.
I'm not sure if this was intended or not, but this is a common NIMBY refrain. The argument of "This thing being advocated for that I'm fighting against isn't something people want anyway". And like walkable neighborhood architecture, extremely few Americans have access to light rail. Let alone light rail that doesn't have to yield to car traffic.
Regardless, the cost arguments fall apart once you take the total cost society pays for each system instead of only what the government pays. Because when you get the sum of road construction & maintenance, car acquisition, car maintenance, insurance, and parking, it dwarfs the cost of the local transit system. Break it down on a per-consumer basis and it gets even uglier. New York City is a good example to dive into, especially since it's the typical punching bag for "out-of-control" budgets.
Quick napkin math pins the annual MTA cost at $32-$33 billion and the total cost of the car system between $25 and $44 billion per year. Since the former serves somewhere around 5.5 million riders, and the latter only about 2 million, the MTA costs $5,300-6,600 per user annually where the car system costs $12,000–$22,500 per user annually.
I'm NOT saying "people don't want to ride trains."
I AM saying "people don't want ride trains that allow 5% of the riders to smoke cigarettes on enclosed train platforms and in enclosed train cars."
You might says "what? but that's not happening."
In Chicago, yes it is: https://resphealth.org/snuff-out-smoking-on-cta/
People want transit as long as that transit reasonably meets their quality of life standards. The reason why automobiles have been so popular -- even while being wildly more expensive -- is exactly that they allow the user to adjust their travel to their optimal quality of life expectations.
Public transit advocates need to be honest with themselves that anti-social behavioral issues really matter to people. People are willing to pay more to have a more pleasant experience. When a transit system fails to meet that standard, then you'll suddenly find yourself with a transit system that people don't want to use.
Just don't allow that then?
> Public transit advocates need to be honest with themselves that anti-social behavioral issues really matter to people. People are willing to pay more to have a more pleasant experience. When a transit system fails to meet that standard, then you'll suddenly find yourself with a transit system that people don't want to use.
"we can't have good transit because a few people who call themselves transit advocates have bad opinions" is very defeatist. Weak-spined politicians find it much easier to just set money on fire than actually solving problems, so even though most transit advocacy groups in the US emphasize quality and being less wasteful with budgets, your politicians usually prefer the worse options.
>Just don't allow that then?
>"we can't have good transit because a few people who call themselves transit advocates have bad opinions" is very defeatist.
My point here is only that this is a hard problem, not a trivial one. When the transit advocates in my area just say "transit should be free" in response to "transit pricing is a complex problem that affects system fragility" and they say "stop hating homeless people" in response to "quality of life concerns matter to keeping the system functional long term" then we're in bad place, because the non-transit advocates literally want to get rid of the system. The last TWO Muni funding bills in SF failed.
We've built a system that can fail catastrophically, in large part, because transit advocates don't want to deal with the realities of running a functional transit system. This is why I get grumpy when people say "all this work is impressive, but I'd rather have better trains" when it's very clear why Waymo is succeeding as Muni is failing, but it is exactly because Muni is mostly disconnected from market forces that we've got to this place, and the "solution" being proposed by most transit advocates is to just completely remove all market forces which will very obviously be worse is the long run.
It's just that Cars have rotted the American mind so much that to consider anything else is sacrilege.
Why do you expect them to make money? Roads don't make money and no one thinks to complain about that. One of the purposes of government is to make investment in things that have more nebulous returns. Moving more people to public transit makes better cities, healthier and happier citizens, stronger communities, and lets us save money on road infrastructure.
I don't.
That's why I said "variable cost of operations."
If a system doesn't generate enough revenue to cover the variable costs of operation, then every single new passenger drives the system closer to bankruptcy. The more "successful" the system is -- the more people depend on it -- the more likely it is to fail if anything happens to the underlying funding source, like a regular old local recession. This simple policy decision can create a downward economic spiral when a recession leads to service cuts, which leads to people unable to get to work reliably, which creates more economic pain, which leads to a bigger recession... rinse/repeat. This is why a public transit system should cover variable costs so that a successful system can grow -- and shrink -- sustainably.
When you aren't growing sustainably, you open yourself up to the whims of the business cycle literally destroying your transit system. It's literally happening right now with SF MUNI, where we've had so many funding problems, that they've consolidated bus lines. I use the 38R, and it's become extremely busy. These busses are getting so packed that people don't want to use them, but the point is they can't expand service because each expansion loses them more money, again, because the system doesn't actually cover those variable costs.
The public should be 100% completely covering the fixed capital costs of the system. Ideally, while there is a bit of wiggle room, the ridership should be 100% be covering the variable capital costs. That way the system can expand when it's successful, and contract when it's less popular. Right now in the Bay Area, you have the worst of both worlds, you have an underutilized system with absolutely spiraling costs, simply because there is zero connection between "people actually wanting to use the system" and "where the money comes from."
Between toll roads, and the toll lanes, they do?
"The total annual cost for road maintenance in the U.S. is in the hundreds of billions of dollars, with estimates showing over $200 billion spent yearly".
Roads are used and essential to every single person whether they use a car or not. Every single product you consume was transported over roads.
Drivers are the problem, not roads. Drivers kill, maim, pollute, and disturb the peace in ways AVs do not.
1) is a bit simplistic though. I don't know of any European system that would cover even operating costs out of fare/commercial revenue. Potentially the London Underground - but not London buses. UK National Rail had higher success rates
The better way to look at it imo is looking at the economic loss as well of congestion/abandoned commutes. To do a ridiculous hypothetical, London would collapse entirely if it didn't have transit. Perhaps 30-40% of inner london could commute by car (or walk/bike), so the economic benefit of that variable transit cost is in the hundreds of billions a year (compared to a small subsidy).
It's not the same in SFBA so I guess it's far easier to just "write off" transit like that, it is theoretically possible (though you'd probably get some quite extreme additional congestion on the freeways as even that small % moving to cars would have an outsized impact on additional congestion).
You're making my argument for me. Again, my concern isn't the day-to-day conveniences of funding, my point is that building a fragile system (a system where the funding is unrelated to the usability of the service) is a system that can fail catastrophically... for systems where there are obviously alternatives (say, National Rail which can be substituted for automobile, bus, and airplane service) are less to worry about, because their failure will likely not cause cascading failures. When an entire local economy is dependent on that system -- when there are not viable substitutes -- then you're really looking at a sudden economic collapse if the funding source runs dry, or if the system is ever mismanaged.
This is a big deal. When funding really actually does run out and the system fails, then if the result is an economic cascade into a full blown depression, then you would have been much better off just building the robust system in the long term. I just really don't think people appreciate how systems can just fail. Whether it's Detroit or Caracas, when the economic tides turn in a fragile system people can lose everything in a matter of a few years.
And National Rail isn't replaceable at all with bus/cars/planes. You really underestimate the number of people which commute >1hr into London (100km+). There is just no way to do that journey by car or bus. It would turn a ~1hr commute into a 3hr _each way_ and that's not even considering the complete lack of parking OR the fact suddenly the roads would be at (even more) gridlock with many multiples of commuters.
That's not even getting into what you consider fixed vs variable costs. Are the trains themselves a fixed cost (they should last 30-40 years)? Is track maintenance a fixed cost (this has to be done more often than the trains themselves), etc etc. The 2nd point is very important - a lot of rail operators in the UK can be made profitable or not on your metric by how much the government subsidises track maintenance vs the operators paying for it in track access charges.
Equally, are signalling upgrades (for example) fixed costs? But really they are only required to run more frequent services. So you could argue they are a variable cost?
Yes
>Is track maintenance a fixed cost (this has to be done more often than the trains themselves)
Yes
>Equally, are signalling upgrades (for example) fixed costs?
Yes
Fixed costs are the costs that don't go away when the passengers go away. Variable cost, typically labor, go away when you don't actually need that additional marginal train. You still have to amortize that train even if it's not on the tracks. You still need to buy that marginal train when the service levels require it. You still have to do track maintenance even when you're not running trains (though, yes, at the very margin there could be some small rate adjustments). When you want to upgrade the signals, it's basically the definition of a fixed cost, because you do it once and it's done.
>And National Rail isn't replaceable at all with bus/cars/planes. You really underestimate the number of people which commute >1hr into London (100km+). There is just no way to do that journey by car or bus. It would turn a ~1hr commute into a 3hr _each way_ and that's not even considering the complete lack of parking OR the fact suddenly the roads would be at (even more) gridlock with many multiples of commuters.
I don't want to speak to National Rail or British Rail that preceded it. I want to stick to the transit system that I know well.
My point here isn't that money shouldn't be spent on "getting things back in shape" here is where I waffle on the "pay for fixed capital costs and mostly have the marginal variable costs covered by the marginal rider." If a system needs the occasional cash infusion, I'm fine with that, as long as it comes with new leadership.
My concern here is that, in the Bay Area, many, many people are eager to pay $25 for a Waymo to pick them up (they are NOT cheap) while Muni costs $3 (a near 10x increase in cost). When folks are willing to pay that much of a premium, then something is very wrong with the transit system. Muni has had zero enforcement of their code of conduct for decades. When you have a system that are large section of the populous actively avoid when it's perfectly convenient, then something is very wrong with the system.
When I see BART stations that look like abandoned parking lots surrounded by single family home sprawl, then it doesn't surprise me that the system is not sustainable. The stations that may get removed are all in areas that require people to drive, to then take the train, instead of the cities zoning density and retail around the train stations. When I yell at the occasional people smoking in BART stations and I go to tell the station attendant and get a shrug back -- even when we are paying for them to have their own police force -- that's why they are failing. These are political choices that BART has made in how they operate their service
These systems aren't even doing the bare minimum in providing a reliable pleasant service, so people stop using them, and that makes sense. The entire point is that these services should be relatively inexpensive to operate because of economies of scale, but when you don't actually make people pay, when you don't actually ask people to behave like responsible adults, when your running the service like a failing business then we should expect the service to fail, and when it does, when bailouts are needed, they should (and often do) come with strings attached. BART now has gates that stop most turnstile jumping... and they were forced to be installed by the state of California as part of their second bailout. The reason I'm harping on having variable costs attached to ridership is exactly because the systems needs to be forced to respond when a sizable amount of people no longer find the service valuable.
This is about sustainability, because the marginal tax dollar is better spend on something like providing people with the healthcare they need than it is providing people a bus service they're not even willing to actually use.
When ridership plummeted by >50% during the pandemic, fixed costs stayed the same, but income dropped. Last time I checked, if Bart ridership returned to 2019 levels, with no other changes, it would be profitable again.
BART has already been bailed out by the state, twice. It has already failed, twice. It very much needs to reduce the level service it provides if it wants to be sustainable, or seek other forms of revenues while we wait to see if ridership returns. Many have suggested BART explore the SE Asian model of generating revenues by developing residential housing, which seems fairly straightforward.
If ridership never returns, then we ought not continue throwing good money after bad, and we ought to adjust the level of service to meet the level of revenues. Obviously the main problem here is that it's literally illegal to just build high density corridors directly adjacent to the transit stations... which is what we ultimately need to prioritize.
> BART, Muni, Caltrain, AC Transit — which an independent analysis confirmed face annual deficits of more than $800 million annually starting in fiscal year 2027-28
https://www.usatoday.com/story/news/california/2026/01/06/ba...
Nearly a billion dollar shortfall per year going forward. That’s nontrivial, and the state has lost patience with the systems after providing two bailouts already.
1. You want to be forward looking, not backwards looking. Cutting services means less ridership means less revenue means cutting services means...etc. Bart is super useful for me during the week because headways from SF to West Oakland are often 5m. As I'm writing this (11 on a Friday) I missed a train and had to wait 20 minutes. Every seat on the car is also full, and while not packed, it's standing room only. If my choice is to wait 20 mins for the next train, other ways of getting places become a lot more appealing.
2. Government services should be good. This is good both because it makes people interested in using them (see 1) and because people who don't have other options deserve good services. The point of government is, at least in part, to serve those who can't serve themselves. I don't expect Bart to be revenue neutral for the same reason I don't expect CalFRESH to be.
That's not true. If you have stations that are revenue positive and stations that are net negative, then cutting ridership at the net-negative stations can put the system in a much better financial position. E.g. If BART didn't end at Antioch, and instead continued to Rio Vista, it's entirely likely that the Rio Vista station would just cost more to operate than is worth operating. It takes time to go back and forth, nobody will ever want to be picked up there because it's car-dependent sprawl. Maybe have one or two stops there during rush hour, but you'll likely be better financially cutting most service.
>headways from SF to West Oakland are often 5m
Nobody is suggesting cutting service between SF and Oakland. I'm sure it's a wildly profitable route. Crossing the bay is the main benefit of BART.
>The point of government is, at least in part, to serve those who can't serve themselves. I don't expect Bart to be revenue neutral for the same reason I don't expect CalFRESH to be.
I also don't expect BART to be revenue neutral. I expect it to be funded -- in very large part -- by taxes. I'm only arguing it should be sustainable. It shouldn't get to the point of literal collapse during economic downturns (again, it's already been bailed out by the state and feds, twice, in the last six years).
I really don't think people realize what I'm getting at. I'm saying the system needs to be functional and needs to function long term. Yes, I think we should subsidize low-income users. Yes, I think people who can't afford it should still be able to use it. But that has to happen in a way that doesn't drive away significant numbers of other users. There's nothing about being low-income that means anti-social. I'm talking about anti-social behavior. I'm talking about people smoking cigarettes and using drugs on BART platforms and in BART cars. I'm talking about people who are actively bothering significant numbers of people around them by their behavior -- behavior that is against BART policy, but is tolerated.
You can't sit here and tell me the current system is working when BART is perpetually collapsing. I care about BART. That's why I'm articulating the systemic problems in the system.
I don't think this follows. Government budgeting isn't zero based. A hypothetical Bart with 2x the government funding in 2019 would have faced cutbacks, but likely has more money today than what we have now!
> or seek other forms of revenues while we wait to see if ridership returns.
Yes, this is called "taxes".
> If ridership never returns, then we ought not continue throwing good money after bad
Agreed if it was stagnant, but ridership is up more than 10% y/y and that was also true last year. It's on track to be revenue neutral again in a few years. Gutting services today would be exactly opposite of what you'd do for something like a startup showing clear path toward profitability.
> Obviously the main problem here is that it's literally illegal to just build high density corridors directly adjacent to the transit stations... which is what we ultimately need to prioritize
While sure it's hard, there's lots of these that exist. There's new stuff in oakland basically constantly, and were even seeing midrise stuff along Bart in SF, but it's units being built now, so they won't be available until 2027, which is when your proposed service cuts would hit.
A hypothetical BART with 2x the government funding wouldn't have existed... because it didn't exist.
>Agreed if it was stagnant, but ridership is up more than 10% y/y and that was also true last year. It's on track to be revenue neutral again in a few years. Gutting services today would be exactly opposite of what you'd do for something like a startup showing clear path toward profitability.
You're mistaking what I'm saying. I want BART to flourish, but I want it to be sustainable. The choice isn't "keep it open" or "close it." How it is operated matters significantly. I'm very obviously going to vote to increase funding, my point is that it shouldn't have to come to a vote. If service is reduced to a more sustainable rate, the system could recover organically. The revenue jump that has happened at stations immediately after the gates were installed, for example, shouldn't surprise anyone. I'm a transit advocate, BART is mostly irrelevant to this discussion anyway, because we're talking about situations where Waymo is a viable alternative, which really doesn't apply to BART.
Rich people want their own methods of highly convenient transportation; they don't want to share with everyone else. They don't pay taxes. Public infra gets worse and the average person taking public infra is poorer. Over time your city has people who don't have houses or jobs, or who do drugs. Inevitably they are relegated to public spaces since they own nothing. The rich people avoid interactions with the poorer members by building gated communities and private infrastructure--rich techies now have concierge physicians and monopolize high quality teaching at their absurdly expensive private schools. Each decision is rational. This is the social rot that is wrought by an oligarchic, and generally value-extracting rentier class.
Many problems today stem from wealth inequality.
That's before you consider how it takes 2-4x as long to get somewhere by public transit outside of peak hours and/or well-covered areas. A 20 minute trip from a bar in Queens to Brooklyn by car takes an hour by train after 2300, not including walking time. I made that trip many, many times, and hated it each time.
I don't want to hear tiktok or full volume soap operas blasting at some deaf mouth breather.
I don't want to be near loud chewing of smelly leftovers.
I don't want to be begged for money, or interact with high or psychotic people.
The current culture doesn't allow enforcement of social behaviour: so public transport will always be a miserable containment vessel for the least functional, and everyone with sense avoids the whole thing.
I quite agree with the overall point but can we leave this kind of discourse on X, please? It doesn't add much, it just feels caustic for effect and engagement farming.
We also police driving behaviour, in a way that nobody does for public behaviour.
And no matter what I don't have to hear or smell other drivers.
Automobiles are a wildly inefficient and expensive form of transportation in urban areas. At the same time, we ought to be willing to ask why a significant amount of our urban population still prefers to pay all that extra money to sit in traffic.
Or the majority of the residents of New York City on their daily commute? I like to think I have sense, and I happily use public transport most days. I prefer it to sitting in traffic, isolated in a car. At least I can read a book. If you work too hard to insulate yourself from the world, the spaces you'll feel comfortable in will get more and more narrow. I think that's a bad thing.
That's the whole problem. Car transportation simply doesn't scale, so there will never be an option to use waymo that's as fast and cheap as the subway. It's worth calling out that an efficient train system is vital to keeping car traffic moving quickly, because once everyone is in a car, it's gridlock.
Living there, without the means to avoid public transport is something I would also consider insane.
Even though the train system in Japan is 10x better than the US as a whole, the per-capita vehicle ownership rate in Japan is not much lower than the US (779 per 1000 vs 670 per 1000). It would be a pipe dream for American trains/subways to be as good as Japan, but even a change that significant would lead to a vehicle ownership share reduced by only about 13%.
I’d much rather have my own vehicle than share my space with a bunch of people.
IMO, access to DeepMind and Google infra is a hugely understated advantage Waymo has that no other competitor can replicate.
Waymo's fleet is ~700 cars. The internet has millions of hours of driving footage. This technique turns the entire internet into a sensor suite. That's a bigger deal than the simulation itself.
A power outage feels like a baseline scenario—orders of magnitude more common than the disasters in this demo. If the system can’t degrade gracefully when traffic lights go dark, what exactly is all that simulation buying us?
https://www.reddit.com/r/SelfDrivingCars/comments/1pem9ep/hm...
That is, both are true: this high-fidelity simulation is valuable and it won't catch all failure modes. Or in other words, it's still on Waymo for failing during the power outage, but it's not uniquely on Waymo's simulation team.
____.----.____
______/ \______
_____/ \_____
________________________________________
(simulations) (real world data) (simulations)
We started with physics-based simulators for training policies. Then put them in the real world using modular perception/prediction/planning systems. Once enough data was collected, we went back to making simulators. This time, they're physics "informed" deep learning models.
Seems like there ought to be a name for this, like so-and-so's law.
https://deepmind.google/blog/genie-3-a-new-frontier-for-worl...
Discussed here,eg.
Genie 3: A new frontier for world models (1510 points, 497 comments)
https://news.ycombinator.com/item?id=44798166
Project Genie: Experimenting with infinite, interactive worlds (673 points, 371 comments)
From the perspective of enactivism and radical empiricism, intelligence doesn't "represent" the world; it simply navigates it. A biological organism doesn't need a 3D CAD file of a tree to survive; it only needs a history of sensory-motor contingencies—the "if I move this way, I see that" patterns. It’s a synthesis of interactions, not a library of blueprints.
AI operates on the same logic, albeit through a different medium. It isn't simulating the physical laws of the universe or "understanding" gravity. Instead, it navigates the high-dimensional geometry of human data. It’s a sophisticated engine of association, performing a high-speed synthesis of the patterns we've left behind.
In this view, "knowing" isn't about matching an internal image to an external truth. It is the seamless flow of past inputs into future predictions. There is no world model—only the habit of being.
I also said it wouldn’t matter if they’re fast, I don’t care about driving at the limit of grip here, just avoiding accidents.
> there's probably no examples in the training data where the car is behind a stopped car, and the driver pulls over to another lane and another car comes from behind and crashes into the driver because it didn't check its blindspot
This specific scenario is in the examples: https://videos.ctfassets.net/7ijaobx36mtm/3wK6IWWc8UmhFNUSyy...
It doesn't show the failure mode, it demonstrates the successful crash avoidance.
As always tho the devil lies in the details: is an LLM based generation pipeline good enough? What even is the definition of "good enough"? Even with good prompts will the world model output something sufficiently close to reality so that it can be used as a good virtual driving environment for further training / testing of autonomous cars? Or do the kind of limitations you mentioned still mean subtle but dangerous imprecisions will slip through and cause too poor data distribution to be a truly viable approach?
My personal feeling is that this we will land somewhere in between: I think approaches like this one will be very useful, but I also don't think the current state of AI models mean we can have something 100% reliable with this.
The question is: is 100% reliability a realistic goal? Human drivers are definitely not 100% reliable. If we come up with a solution 10x more reliable than the best human drivers, that maybe has some also some hard proof that it cannot have certain classes of catastrophic failure modes (probably with verified code based approaches that for instance guarantees that even if the NN output is invalid the car doesn't try to make moves out of a verifiably safe envelope) then I feel like the public and regulators would be much more inclined to authorize full autonomy.
[1] I've seen a couple of them but they're not available to hire yet and are still very rare.
Or the most realistic game of SimCity you could imagine.
They're implying that without the model having knowledge, even approximate, of a scene to react to, it simply doesn't react at all; it simply "yields" to the situation until it passes. In my experience taking Waymo's almost daily this holds.
I would rather not have the Waymo yield to a tornado, rising flood-waters, or charging elephant...
"we’re excited to continue effectively adapting to Boston’s cobblestones, narrow alleyways, roundabouts and turnpikes."
edit: Case in point:
https://maps.app.goo.gl/xxYQWHrzSMES8HPL8
This is an alley in Coimbra, Portugal. A couple years ago I stayed at a hotel in this very street and took a cab from the train station. The driver could have stopped in the praça below and told me to walk 15m up. Instead the guy went all the way up then curved through 5-10 alleys like that to drop me off right right in front of my place. At a significant speed as well. It was one of the craziest car rides I've ever experienced.
Anyway, we'll see how the London rollout goes, but I get the impression London's got a lot more of those kinds of roads.
That is extremely narrow, I wonder why the city has not designated it as a one-way street? They've done that for other similarly narrow sections of the same street farther north.
The trick to UK streets is that parking actually happens on the street itself, and when driving you must find a spot when people are not parking to make way for people coming the other way.
Human drivers routinely do worse than Waymo, which I take 2 or 3 times a week. Is it perfect? No. Does it handle the situation better than most Lyft or Uber drivers? Yes.
As a bonus: unlike some of those drivers the Waymo doesn't get palpably angry at me for driving the route.
Not taking paying passengers yet though!
For shits and giggles, I did stop randomly while crossing the road and acted like a jerk.
The Waymo did, in fact, stop.
Kudos, Waymo
That said, for autonomous driving I'd like to see as many sensor options as possible: lidar, radar, cameras, sonar. Belt and suspenders. I imagine as pricing continues to drop all will be embraced.
In the example videos, the Golden Gate bridge with snow shows the bridge as 1 road, with total of 3 lanes. But in reality, it’s a split highway with divider, so 2 sides both have 3 lanes, 6 total lanes.
What happens when the car “learns” to drive on the simulated incorrect 3 lane example? For example will next time it goes on the real GG bridge hug to the rightmost lane?
This would give the ability to see things other cars cannot see as well.
2. No seriously, is the filipino driver thing confirmed? It really feels like they're trying to bury that.
But pedestrian infrastructure is a very simple problem to solve, even in the US. Just look at how the market responds to public transit projects in the US —- developers trip over themselves to build projects in response to the induced demand.
Likewise they also responded to the reduced demand as a result of ripping out public transit infrastructure in the 20th century. Which is why doughnut-shaped cities are common in the US.
Once it gets unstuck, it runs autonomously.
The technology "feels" way less cool knowing that there are human backups, which would absolutely in turn make its percieved value go down.
But eventually I think we will get there. Human drivers will be banned, the roads will be exclusively used by autonomous vehicles that are very efficient drivers (we could totally remove stoplights, for example. Only pedestrian crossing signs would be needed. Robo-vehicles could plug into a city-wide network that optimizes the routing of every vehicle.) At that point, public transit becomes subsidized robotaxi rides. Why take a subway when a car can take you door to door with an optimized route?
So in terms of why it isn’t a waste of time, it’s a step along the path towards this vision. We can’t flip a switch and make this tech exist, it will happen in gradual steps.
I basically agree with your premise that public transit as it exists today will be rendered obsolete, but I think this point here is where your prediction hits a wall. I would be stunned if we agreed to eliminate human drivers from the road in my lifetime, or the lifetime of anyone alive today. Waymo is amazing, but still just at the beginning of the long tail.
- I would be stunned if we agree to eliminate human drivers from 100% of roads in the lifetime of anyone alive today.
or
- I would be stunned if we agree to eliminate human drivers from 10% of roads...
...or is there some other percentage to qualify this? I guess I wouldn't expect there to be a decree that makes it happen all at once for a country. Especially a large country like the U.S.. More like, some really dense city will decide to make a tiny core autonomous vehicles only, and then some other cities also do years later. And then maybe it expands to something larger than just the core after 5 or 10 years. And so on...
And in the spirit of that nuance, I will revise my statement slightly. I think it is entirely possible we will eliminate drivers on 10% of roads. We have rules that are analogous to that already with limited access highways. Though I would rate this still as unlikely, since such roads only make up just over 1% of all the roads in the US as it is. Not sure what the % is for other countries, probably less.
> some really dense city will decide to make a tiny core autonomous vehicles only
Agree 100%, this kind of thing I do expect to see happen. We already have exclusions for cars altogether in favor of pedestrians, so the precedent is set.
It basically happened for horses.
Automation makes public transit better. There will be automated minibuses that are more flexible and frequent than today's buses. Automation also means that buses get a virtual bus lane. Taxis solve the last mile problem, by taking taxi to the station, riding train with thousands of people, and then taking more transit.
Also, we might discover the advantage of human powered transit. Ebikes are more efficient than cars and give health benefits. They will be much safer than automated cars. Could use the extra capacity for bike and bus lanes.
In my sleepy metro area that has at least mid-tier respectable public transit (by US standards only), otherwise known as Portland, I think a lot of the routes would be better served by minibuses than full size. I wonder how the economics work out on that. Maybe dominated by labor? Tri-met drivers have a reputation of being paid handsomely as they gain seniority.
Fundamentally impossible. You're moving some 2 tons of mass in a 2x5m box on polluting rubber tires to move a single 100kg human.
I can always take whatever efficiency gain you've thought up and simply make the vehicle bigger, decreasing the cost and space used per passenger, and maybe even put it on rails, making it less polluting, and more energy efficient.
You can't engineer your way out of the laws of physics.
And don't even get me started on e-bikes.
In high density regions, vehicles on surface roads can’t meet the passenger demand required. Even if you banned human drivers, the other human users introduce too much variability and delay (passengers loading and unloading, errant objects, cyclists and pedestrians, etc). Roll a dumpster in the street, and have a couple of jaywalkers, and the entire system crawls to a stop.
Controlled access is required to get even medium-high throughput. But these systems already exist, they are called personal rapid transit systems.
Anyway you can think it's a waste but they're wasting their money, not yours. If you want a train in your town, go get one. Waymo has only spent, cumulatively, about 4 months of the budgets of American transit agencies. If you had all that money it wouldn't amount to anything.
Oh come on -- of course they are. That's precisely why you put it in a "white paper" and not, you know, ads.
For context, my "driver's test" was going to the back of the office, and driving some old car backwards and forwards a few meters.
Not for the rendering (that's still way too expensive), but for the initial world generation that gets iteratively refined and then still ultimately gets converted into textured triangles.
Almost all video game environments? No way. That statement really needs to be qualified with the genres of games you're considering.
Even if you can generate simulated training data, don't you still have the problem where you don't even know what the edge cases you need to simulate are in the first place?
It just strikes me as neverending edge case wack-a-mole
A human doesn't need to see tons of examples of tornados and elephants to know to stop the car
Doesn't that indicate some fundamental difference between the model and a human driver?
Also, even if the car behaved perfectly anyway, these scenarios are useful for testing — validating that the expected behavior happens.
It’s practically infinite, your domain is 3D space and time
You can’t just generate every possible scenario
That would be a combinatorially insane amount of data
[1] https://people.com/waymo-exec-reveals-company-uses-operators...
edit: fixed kill -> hit
Under the same circumstances (kid suddenly emerging between two parked cars and running out onto the street), it could be debated that the outcome could have been worse if a human were driving.
[1] https://people.com/waymo-car-hits-child-walking-to-school-du...
It really looks like waymo is the one going in the wrong direction and driving dangerously to evade traffic in this simulation.
I started working heavily on realizing them in 2016 and it is unquestionably (finally) the future of AI
I think you meant, "Attempt" to limit what people can do.
Driving in SF (for example) provides many opportunities to see "free will" exerted in the most extreme ways -- laws be damned.
Disabled and then loaded into a lead-lined trailer or something.
I imagine the IP running locally on the cars is worth billions.
I also doubt the IP is worth that much. Most of the secret sauce to starting a competitor probably isn't an end model tuned for a specific configuration of a car but the ability to produce end models, which wouldn't be stealable from the car.
That thing I called full self driving just to troll government regulators? Just make it work and don't complain about what I called it.
That rocket that's way too big for orbital payloads but can't go beyond orbit without sending 20 more rockets full of fuel? Just make it work. Occupy Mars!
The two car models that work and have a halo effect on the rest of the product line? I'mma cancel that! Just make the stupid truck we're keeping work!
We've all had a boss like that. I'm sure they salute each other.
Its much easier to build everything into the compressed latent space of physical objects and how they move, and operate from there.
Everyone jumped on the end-2-end bandwagon, which then locks you into the input to your driving model being vision, which means that you have to have things like genie to generate vision data, which is wasteful.
Basically, driving policy needs to be MCTS search on a space that represents physical objects.
If I were to build a self driving system here is how I would do it:
* Define a 3d representation of the physical space around the car and how it evolves. Basically a very compressed simulator that has an input of initial conditions, and then predicts the evolution of the scene. The big difference here is that you would be manually coding this sim (i.e not training it), because you would be defining rules for things like collisions. You can also conveniently integrate your car control in this sim, with motion based on tire behavior that happens when you turn the steering wheel.
* Build probablistic behaviour of other objects (i.e cars/pedestrians) from real world driving data. I.e given a time span of driving, these essentially represent the probability of what the human pedestrian or the human driver would do.
* On the sensor side, you would train models to take lidar/camera and create the initial conditions for the sim. I.e things like big trucks would map to big trucks with a lot of mass and inertia, things like obstruction on the road would represent essentially "walls" that you cannot hit, and traffic control objects that represent "soft" boundaries.
* On the driver side, you would train something like MuZero to essentially play the driving game within the sim, building both the prediction model at training, and at inference time running MCTS to chose the best optimal policy. Scoring would be done based on things like following traffic control signals and not hitting things, minimizing traffic disturbance, following the GPS route, and so on e.t.c.
And this is how you would get superhuman driving. Just like in the cases where a neural net learns to play a particular game and finds really unique strategies, you would see similar things with this. For example, It would be able to avoid collision situations where you would get rear ended, because it would predict a collision, see that emergency lane is open, and create a control plan to move the car out of the way. And from a product perspective, you can imagine how advantageous this would be in terms of development and improvement.
And to answer your question, you wouldn't really even need to do end to end as a test for bugs, you would just need to make sure your sensor model is accurate, which can be done simply by driving the car and it observing the world. Its much simpler to do than comparable systems because you don't care about what the object is, you just care whether its part of the terrain or not, and if its not, you really just care about its size in terms of taking up space and its trajectory.
This is legit hilarious to read from some random HN account.
Humans don't drive well because we map vision policy to actions. We drive well (an in general, manipulate physical objects well), because we can do simulations inside our head to predict what the outcome will be. We aren't burdened by our inability to recognize certain things - when something is in the road, no matter what it is, we auto predict that we would likely collide with that thing because we understand the concept of 3d space and moving within it, and take appropriate action. Sure, there is some level of direct mapping as many people can drive while "spaced out", but attentive driving involves mostly the above.
The self driving system that can actually self drive needs to do the same. When you have this, you will no longer need to do things like simulate driving conditions in a computationally expensive sim. You aren't going to be concerned with training model on edge cases. All you would need to to ensure that your sensor processing results in a 3d representation of the driving conditions, and the model will then be able to do what humans do and explore a latent space of things it can do and predict outcomes then chose the best one.
You want proof? It exists in the form of Mu Zero, and it worked amazingly well. And driving can be easily reformated as a game that the engine plays in a simulator that doesn't involve vision, and learns both the available moves and also the optimal policy.
The reason everyone is doing end to end today is because they are basically trying to catch up to Tesla, and from a business perspective, nobody is willing to put money and pay smart enough people to research this, especially because there is also a legal bridge to cross when it comes to proving that the system can self drive while you napping. But nevertheless, if you ever want self driving, this is the right approach.
Meanwhile, Google who came up with Mu Zero, is now doing more advanced robotic stuff than anyone out there.
What on earth? We already have this, it’s called Waymo. And the idea that they’re trying to catch up to Tesla is laughable.
[*] https://futurism.com/advanced-transport/waymos-controlled-wo...
Having humans in the loop at some level is necessary for handling rare edge cases safely.
The first is the DDT control loop, what a human driver does. Waymo's remote assistants aren't involved in that. The computer always has responsibility for the safety of the vehicle and decisionmaking while operating, which is why Waymo's humans are remote assistants and not remote drivers. Their safety drivers do participate in the DDT loop, hence the name.
But there's also another "loop" of human involvement. Sometimes the vehicle doesn't understand the scene and asks humans for advice about the appropriate action to take. It's vaguely similar to captchas. The human will usually confirm the computer's proposed actions, but they can also suggest different actions. The computer the advice as a prior to continue operating instead of giving up the DDT responsibility. There's very likely a closely monitored SLA between a few seconds to a few minutes on how long it takes humans to start looking at the scene.
If something causes the computer to believe the advice isn't safe, it will ignore it. There have been cases where Waymos have erroneously detected collisions and remote assistants were unable to override that decisionmaking. When that happens, a vehicle recovery team is physically sent out to the location. The SLA here is likely between tens of minutes and a couple hours.
Listen to the statement.
The operators help when the Waymo is in a "difficult situation".
Car drives itself 99% of the time, long tail of issues not yet fixed have a human intervene.
Everyone is making out like it's an RC car, completely false.
And apparently some people still haven't caught on.
Have a look if you don't believe me:
https://hn.algolia.com/?dateRange=custom&page=0&prefix=false...
Talk about edge cases.
But, what would you do? Trust the Waymo, or get out (or never get in) at the first sign of trouble?
This does bring up something, though: Waymo has a "pull over" feature, but it's hidden behind a couple of touch screen actions involving small virtual buttons and it does not pull over immediately. Instead, it "finds a spot to pull over". I would very much like a big red STOP IMMEDIATELY button in these vehicles.
It was on the home screen when I've taken it, and when I tested it, it seemed to pull to the first safe place. I don't trust the general pubic with a stop button.
Vivaldi 7.8.3931.63 on iOS 26.2.1 iPhone 16 pro
It probably doesn't matter though, "this general blob over there"
Also we record body position actuation and self speech. As output then we put this on thousands of people to get as much data as Waymo gets.
I mean that’s what we need to imitate agi right? I guess the only thing missing is the memory mechanism. We train everything as if it’s an input and output function without accounting for memory.
Time to eat pop corn, while FSD drives me for the next hour while I scroll hackernews
Just where lines are and when a car should accelerate or break. The rest of the latent state is "based on pixels."
Self driving cars is a dead end technology, that will introduce a whole host of new problems which are already solved with public transit, better urban planning, etc.
> Redesigning and rebuilding city transportation infrastructure isn't happening, look around.
We have been redesigning and rebuilding city transportation infrastructure since we had cities. Where I live (Seattle) they are opening a new light rail bridge crossing just next month (first rail over a floting bridge; which is technologically very interesting), and two new rail lines are being planned. In the 1960s the Bay area completely revolutionized their transit sytem when they opened BART.
I think you are simply wrong here.
66 years later we see California struggling terribly with implementation of a high-speed rail system -- where the placement/location of the infrastructure largely is targeted for areas far less dense than the Bay Area.
I don't think there is any single reason why this is so much more difficult now then it was in 1960 -- but clearly things have changed quite a lot in that time.
The US already did it once (just in the wrong direction) by redesigning all cities to be unfriendly to humans and only navigable by cars. It should be technically possible to revert that mistake.
Trains need tracks, cars - already have the infrastructure to drive on.
> Self driving cars is a dead end technology, that will introduce a whole host of new problems which are already solved with public transit, better urban planning, etc.
Self driving cars will literally become a part of public transit
I’ve been hearing people say that for almost 15 years now. I believe it when I see it.
I'm willing to wager that you might not actually believe it at that point either.
I would be happy to bet on some strict definition of your claim.
It will prove disruptive to the driving industry, but I think we’ve been through worse disruptions and fared the better for it.
There is no way metro and trains will be a solid way of transportation in LA for at least a few more decades, even if people of Bel-Air stop fighting trains that go deep under Bel-Air and people of valley stop being unreasonable. Even if next president, rollbacks contingency requirement changes that trump did. Even America remember how to build large infrastructure projects.
It will never be the ideal "you're always at most 20-30 minutes of walking away from the station" density here in LA.
> Autonomous private cars is not the technological progress you think it is. We’ve had autonomous trains for decades, and while it provides us with a more efficient and cost effective public transit system, it didn’t open the doors for the next revolutionary technology.
There is a huge difference between going on rails and going on public roads. There are plenty of "dead end technologies" that we use to this day.
Good point. However that does not apply to self driving cars because the problem it is trying to fix is a lot more complex then how to heat your microwave burrito more quickly. Self driving cars shares many of the same problems with human driven cars, including traffic congestion. If we see a mass employment of self driving cars in our cities, these problems will still remain, and the only thing this technology has solved is the need for commuters to pay attention 100% of the way. While nice, that is not revolutionary.
I think you are underselling your city here. LA has an excellent bus system which can be improved further still. LA also has the potential of installing a world class bicycle infrastructure, and me personally I am fairly optimistic that sometime in the near future, your city will put my city of Seattle to shame with your bike network.
No really, insanity that usually happens inside a bus in LA aside, it still goes on the same congested roads. "Bus Only" becomes a suggestion once rush hour starts (I can see bus only line backed up by not buses every day our of my window).
I mostly use metro because buses not worth it for me. Metro network is either wonderful stops or very bad stops. There is a massive "cleanup" attempt before the Olympics. Some will be right where you want to go and some are in the middle of a freeway 20 minutes of walking away from anything.
The fact that K line does not go through Getty Center to please a handful of people and car brains saddens me.
> LA also has the potential of installing a world class bicycle infrastructure
Please no. Cyclists are probably the most hated category on the road even by other cyclists. I'd ban cycling on public roads in most of LA if it were up to me.
As to the revolt, America doesn't do that any more. Years of education have removed both the vim and vigor of our souls. People will complain. They will do a TikTok dance as protest. Some will go into the streets. No meaningful uprising will occur.
The poor and the affected will be told to go to the trades. That's the new learn to program. Our tech overlords will have their media tell us that everything is ok (packaging it appropriately for the specific side of the aisle).
Ultimately the US will go down hill to become a Belgium. Not terrible, but not a world dominating, hand cutting entity it once was.
Sharing one's opinion in a respectful way is possible. Less spectacle, so less eyeballs, but worth it. Try it.
The original Luddite movement arose in response to automation in the textile industry.
They committed violence. Violence was committed against them. All tragic events when viewed from a certain perspective.
My rhetorical question is this: did any of this result in any meaningful impedance of the "march of technological progress"?
The irony
I'm curious why you say this given you start by highlighting several characteristics that are not like Belgium (to wit, poor education, political media capture, effective oligarchy). I feel there are several other nations that may be better comparators, just want to understand your selection.
Same was said about electricity, or the internet.
i dont want my uber driver bragging anout how theyre going to shoot me before i get out of the car
Edit: or are you talking about the allegations of workers in the Philippines controlling the Waymos: https://futurism.com/advanced-transport/waymos-controlled-wo... I guess both are valid.
So maybe unsure is a better term than confused?
We've simply relabeled the "Mechanical Turk" into "AI."
The rest is built on stolen copyrighted data.
The new corporate model: "just lie the government clearly doesn't give a shit anymore."
> After being pressed for a breakdown on where these overseas operators operate, Peña said he didn’t have those stats, explaining that some operators live in the US, but others live much further away, including in the Philippines.
> “They provide guidance,” he argued. “They do not remotely drive the vehicles. Waymo asks for guidance in certain situations and gets an input, but the Waymo vehicle is always in charge of the dynamic driving tasks, so that is just one additional input.”
“When the Waymo vehicle encounters a particular situation on the road, the autonomous driver can reach out to a human fleet response agent for additional information to contextualize its environment,” the post reads. “The Waymo Driver [software] does not rely solely on the inputs it receives from the fleet response agent and it is in control of the vehicle at all times.” [from Waymo's own blog https://waymo.com/blog/2024/05/fleet-response/]
What's the problem with this?