It would be unwise for any company to underestimate their competition.
My perspective as a TSLA shareholder is that any relevant comparison between Tesla's FSD and nVidia's autonomous vehicle platform needs:
to be done by an independent entity,
that has full ability to test each system without influence from either company
Based on current information, this community has no idea which system is better, or whether one system is evolving quickly enough that it could outpace the other over time.
Elon Musk has been incorrect, year after year, about FSD achieving true autonomy.
But we cannot take nVidia's limited demo as proof of anything either.
Almost everyone* has been wrong about autonomy year after year. Waymo, Cruise, etc also had wildly optimistic predictions. Nvidia’s chip is cool, but unless you have a fully integrated system and can scale production profitability then it’s basically a really good demo / lab scale, not a product to be produced in the millions. There’s no reason to expect that this will be done any time soon.
That’s all. They don’t have fully integrated autonomous systems with years of refinement trained on billions of real world miles. Any company trying to compete with Tesla FSD is permanently 5-10 years behind, at least until true human level AGI emerges.
That’s all. They don’t have fully integrated autonomous systems with years of refinement trained on billions of real world miles.
Precisely, and that's what Cosmos and Drive Sim are for. They worked around the problem entirely. No need for billions of miles when you can do distillations of trillions of miles synthetically. Classic example of disruption.
Waymo did much the same thing with MGAIL, ChauffeurNet, MultiPath, SimulationCity, and Waymax. That's exactly how Waymo has been able to put driverless vehicles on the road already while Tesla is still figuring it out — they found a way to skip past the entire "real world miles" problem.
Even if you could skip all the real world training (doubtful) then you still have to manufacture millions of cars with the right sensor suite… so best case (for competitors) this is an issue for Tesla like ~5 years from now?
Xiaomi delivered 400,000 cars with NVIDIA hardware last year, about half of those being Thor-based YU7s. WeRide and Pony are both already driverless on this same hardware stack as well. And of course, every Mercedes CLA being delivered this year (and soon, every GLC) has the NVIDIA stack too.
Geely's Zeekr has Thor in production as well. So does Li Auto. Volvo's ES90 and EX90 already have an Orin package. Rivan's R1S and R1T do too. Lucid's Air and Gravity also.
So... now. The threat is now. Millions of cars will be manufactured this year with sensor arrays and compute packages equivalent to or better than Tesla's. It is not happening five years from now — it is happening now.
“And by 2028, Nvidia predicts its self-driving tech will be in personally owned autonomous vehicles. Also in 2028, Nvidia plans on supplying systems that can enable Level 3 highway driving”
The company who produces this tech is telling you that optimistically it will start rolling out in 2028…
People seem to confuse this all the time… just because something is classified as L2 doesn’t mean the capability is the same. Tesla is capable of L4/L5, right now customers with FSD experience L4 (myself included), but for liability Tesla is leaving it as L2 until they want to take the liability (and likely up the subscription cost). There are millions of these Teslas on the road today. The Nvidia equivalent is going to start to roll out in 2028.
That's not how SAE J3016 works at all. As always, I really recommend that people actually read is — it's way easier to digest than you think. Crack open a beer, spend an evening skimming through it. There's a lot of interesting material within it. At present, Tesla's FSD is a system with L2 features only, it isn't capable of L4. It may eventually have L4 capabilities, but it doesn't have them now.
Separate from what hardware those cars use, and wyamos use, there are multiple other 'car platforms' (car, software, hardware and sensors and cpus on-car) that are working driverless robotaxis in wide use. Several driverless taxi comapnies in china, waymo has reached 1 million paid rides a week.
You seriously believe Tesla choosing to begin service (incredibly wisely) in a small area is equivalent to Waymo relying on LIDAR to precisely geolocate their vehicle in an ultra-high resolution pre-made 3d map of every street, curb, lane line, sign, signal…?
You seriously believe Tesla choosing to begin service (incredibly wisely) in a small area....
Is a geofence. That's what geofencing is. You begin service in an area that is a known quantity to control for unknowns. You expand that geofence as you become confident that environs outside of the initial geofence are now known.
That's what Tesla is doing.
..is equivalent to Waymo relying on LIDAR to precisely geolocate their vehicle
No, I do not — I don't believe it's equivalent because that not what LIDAR is or how it's used. This has been explained to you repeatedly for like six or seven years now. Lidar geolocation reliance isn't a thing and it never has been — these cars are equipped with GPS and they have been from the start. They don't need some sort of strange elaborate rube-goldberg point-cloud machine to geolocate themselves.
If you think using LIDAR as the primary means to located yourself in the world sounds dumb, that's because it is: You've hallucinated an entire architectural choice that never existed.
And you have been repeatedly wrong for years. Now with AI, it is easy to check. Sorry for the loss of formatting.
—————
Waymo's geolocation system uses LiDAR as a core sensor, combining its data with cameras, radar, GPS, and highly-detailed pre-built maps to achieve centimeter-level accuracy. This multi-sensor fusion allows the Waymo Driver to determine its precise position on the road.
How Waymo Uses LiDAR for Geolocation
3D Environment Mapping: Before a Waymo vehicle operates in a new area, the location is manually driven and mapped using sensor-equipped cars. The LiDAR sensors paint a precise, three-dimensional picture of the surroundings, including permanent features like the height of curbs, lane lines, traffic signs, and buildings. This results in a highly-detailed map that has far more information than standard consumer maps.
Real-time Localization: As the autonomous car drives, its onboard computers compare the real-time 3D data from its LiDAR and other sensors with the pre-existing high-definition (HD) maps. By matching the live sensor data to the static map features, the car can pinpoint its location to within 10 centimeters of accuracy.
Reduced Reliance on GPS Alone: While GPS is used, the detailed mapping and LiDAR localization mean the vehicle doesn't solely rely on GPS, which can be less accurate or lose signal in urban canyons or tunnels.
Focus on Dynamic Objects: By knowing the static environment from the map, the system's sensors and software can focus their processing power more effectively on dynamic, moving objects like other vehicles, pedestrians, and sudden changes like construction zones.
A hypocritical statement, given that Tesla also geofences its Robotaxi service.
Elon Musk himself also stated during the Q1 '25 earnings call that it was possible that Tesla would have to customize its trained software to work better in specific locations:
"It does seem increasingly likely that there will be a localized parameter set perhaps sort of … especially for places that have, say, very snowy weather. Like say if you're in the Northeast or something, like there's … you can think of it, it's kind of a human. You could be a very good driver in California, but are you going to be also a good driver in a blizzard in Manhattan? You're not going to be as good."
Haha. Waymo cannot operate outside an area where they have created ultra-high resolution 3d maps of every curb, lane line, signal…
Tesla is merely starting service in a small region before they scale. And customizations to geographic areas to enhance the SW is in a completely different league to only being able to operate in areas where your LIDAR can geolocate you with extreme precision within this pre-created 3-D world. You really should not be investing.
Why in the world are you on a Tesla investors club Forum, if you don’t know, basic information such as this? I’m a firm believer unless you are a complete expert in a company, you should never consider investing. And by complete expert, I mean you have spent thousands of hours of research.
And customizations to geographic areas to enhance the SW is in a completely different league to only being able to operate in areas where your LIDAR can geolocate you with extreme precision within this pre-created 3-D world.
If Tesla has to re-train to get a localized parameter set, how is this fundamentally different than 3D mapping a new area? Both methods require a vehicle or vehicles to drive around the location.
You really should not be investing.
As someone who has been investing since 1997 and retired in 2022, more than 2 decades ahead of schedule, my investing skills are, on the CAGR numbers, far better than the vast majority of both retail and professional money managers.
I've been a TSLA shareholder since 2011, read the SEC filings, and watch the progress of both FSD and facilities construction very closely.
If you don’t understand why adding some custom parameters is different than creating and maintaining a brittle ultra-high definition map, then I can’t help you.
Investing experience does not help with investing in hi-tech companies if you don’t understand the tech.
I don't think the real world miles matter. Even Tesla has simulations set up to help train their systems. I doubt they use the messy data from the fleet as much as you think.
Tesla FSD: already production vehicles deployed vision-only end to end neural network model with ~15B parameters trained on 876,000 hours (100 years) of real world data and simulation data in closed loop, scaling up reasoning in v14.3 deployment in Q1 2026. Currently driving ~450M miles per month, currently scaling a robotaxi service with imminent safety supervisor removal.
Nvidia Alpamayo: training framework and teacher model with 10B parameters (not for direct deployment in production vehicles) for variety of sensor suites trained on 1,700 hours of real world training data and a whole lot of simulation data with chain of thought reasoning. Currently deployed on a few test mules and scaling a pilot program in Q1.
In 2022, they had 1 billion parameters. In August 2024 when they rolled out FSD v12.5.1 they increased the parameters by 5x according to release notes and in November 2024 when they released FSD 13.2, they increased parameters by 3x according to release notes.
We don’t know what happened to the parameter count between 2022-2024. It could have gone up or down, but unlikely down since they went end to end neural network in 2024. That’s why 15B is an estimate, likely a conservative one.
2022 was before end-to-end, so that was the total parameter count of all the neural networks. The first end-to-end neural network came out at the beginning of 2024 with v12. We don't know the size of that initial neural network, so we can't use subsequent increases to calculate the current size.
No idea, honestly. I can see it being smaller because a lot of the old neural networks still need to be running, so there may not have been enough room compute-wise to run all of those and run another neural network equal in size to the previous total at the same time.
That’s some hopium if you think that it is imminent without a safety supervisor. Only thing imminent is a crash when that happens. I have full self driving on HW4. It works amazing 99% of the time until it doesn’t that one time.
Was using it driving back from Virginia Beach this summer, it got confused coming out of a construction zone and went into the shoulder thinking it was a lane bc it was newly painted. Almost drove straight into the railing, it would have split the car.
Some guy posted a video like last week in the Tesla subreddit on just Tesla with fsd blowing a stop sign going 40 mph.
I don't know why people think FSD needs to be perfect to be usable.
Even if it still causes a few deaths every 1 billion miles, it would save many lives and represent a marked improvement over having human drivers who would kill about 15-20 people and injure many more in that same distance.
Not really as you assume drunk drivers don’t still exist as we transition out of human driven vehicles so being 3 times better than a sober human is not good enough. Probably needs to be 10 times better than human for the market class that currently drives Teslas.
No, I assume drunk FSD doesn't exist (because it doesn't).
Drunk drivers are an inherent and inseparable part of the pool of human drivers, including Tesla drivers (non-FSD). So there is no point in isolating and ignoring those drivers for statistical purposes.
If you were to compare FSD to only the best-of-the-best drivers, you'd also have to exclude:
the teenagers,
the elderly,
the texting-addicted,
the easily-distracted,
the plain-bad drivers,
the epileptic,
the diabetic,
the narcoleptic,
etc.,
as if they weren't on the road — which is silly, because we can't prevent them from sharing the road with us.
In fact, those are exactly the drivers we should be moving over to FSD ASAP to make us all much safer.
I think they need to deploy 14.3, which will be a step change in how it drives because it will have 10x more parameters in the neural network and reasoning capabilities. Then they need to validate that for a month or two before removing the safety supervisor. All in all, should be around March/April when the Cybercab starts volume production, otherwise those volume produced cybercabs will be sitting in lots since they don’t have steering wheels.
The end to end neural network, which takes cameras as input, will output reasoning tokens in addition to the controls (steering wheel, acceleration, brake). The reasoning tokens would explain step by step why the car is taking a certain action.
This allows Tesla to better debug why the car makes mistakes when it does, and then train out those mistakes and train out bad reasoning as well, leaving just good driving with good reasoning.
The Austin cars have been automatically taking themselves to problem areas in their geofence to validate training. They'll reach enough safety for unsupervised in that area before they crack everywhere else.
It will become a L4 system this year, and will likely surpass Waymo on at least some metrics (# of cars, # of rides per week, # of cities, or safety stats) this year also.
If not, then I would agree with you in your skepticism going forward
Today they have a bunch of cars going around with safety drivers but you feel confident that they will make big improvements this year and surpass Waymo in some way. Well I admire your optimism..
The safety drivers are not driving the cars though. People want so badly to see and predict the future ahead of the market and here it is on a silver platter for everyone. Don't let your biases fuck you over.
They are sitting there to kill it when it screws up. Its no different from FSD shown for years. Except this is easier because its a geofenced easy area with good weather conditions. Show me it going coast to coast without a single disengagement, then I be impressed. Make it do it 10000 times in all weather and traffic conditions and I maybe start to think its starting to be ready for a release.
Do you not have access to YouTube? It's littered with examples, especially since December. And it has gone coast to coast 100% FSD. The guy who did it posted his telemetry data and all.
Here's another take, Tesla has zero unsupervised miles driven today, same as NVDA.
Now NVDA makes their own chips and can scale the model to infinity because they are not chip constrained. The teacher pupil model scales better due to lower car hardware requirements, once it's distilled small enough it will run on any production car with any sensor kit. This makes them scale up lightning fast.
Tesla has zero unsupervised miles driven today, same as NVDA.
Remember, NVDA isn't offering product directly (B2C). The whole idea is to go through partners (B2B) of which they have many.
There are quite a few NVDA partners using NVDA hardware and software stack modules in L4 production with unsupervised miles. Pony is running NVDA hardware and stack, for instance. Nuro... same. WeRide for another. All of these companies have unsupervised driverless miles. So what you're saying is not true.
That's a doozy of a sentence. Nvidia Drive is an entire platform ecosystem, it isn't just a planning module. There's hardware, software, sample architectures and algorithms, cloud services, a partner tier system, and like ten other levels. It isn't a binary opt-in-opt-out, nor is it contained to a single corner of the stack or implementation. It's more like a framework.
You didn't even know what NVIDIA Drive was a moment ago. It's okay to be out of your depth, but repeatedly bluffing and blustering through the conversation isn't a good look.
Yes, these companies all use NVIDIA as an integral part of their software stack, both training-side and inference-side. That's what DriveOS is. Again, this is an ecosystem. You pick and choose what you want from it, and there are many, many different levels of involvement. At the fundamental, most basic level, nearly all the industry players are using some NVIDIA SDKs/APIs and hardware/software implementations as an integral part of their systems — that's how it's been for years.
Try bullshitting someone else, champ. As I said before — repeatedly bluffing and blustering your way through this conversation isn't a good look, and it isn't going to work.
Tesla is also going to be doing teacher pupil models too if they aren’t already. They have to for the scaled down version of FSD v14 for HW3 vehicles in Q2 of this year.
I would not let my Tesla drive autonomously. Only 1 yr old and it makes the most dangerous decisions even in broad daylight (where lack of lidar wouldn’t even matter).
A look at his other headlines makes it clear what agenda he's pushing. Journalists shouldn't be pushing any agenda, to be clear, but man is he transparent.
Title is copy+pasted from the article, I figure it'll rub some people on the sub the wrong way but I'm following Rule 4.
I personally don't find NV's competition concerning given Tesla's ability to scale - my belief for a decade has always been that every software company would hit L4 within the span of a year or two - this is how the entire history of software has gone, and we've seen the same with AI across the industry... So the limiting factor becomes # cars produced which Tesla can excel at. Full disclosure I'm pretty heavy on TSLA NVDA and GOOG stock though I'm not really invested for NV's autonomy or Waymo. AI is going to take off and there will be many winners, IMO whoever has talent and a path to $ will win.
Have any of them demonstrated over the air updates? It isn't just the computer but all vehicle controllers that need to integrate including camera variants and positions.
I think OP undersells how hard building the software is that can handle proper L4, and oversells how copy able it will be. But I agree that we won't see one company standing alone with L4 for very long, so I agree that in and off itself can't be why you value a company highly.
If Tesla has any shot of living up to the valuation it will need to trigger Elon's pay package then the play is around the fleet and in particular charging. No other competitor has a charging network of their own design. If Tesla can automate charging alongside robotaxi, L4 and long range banish/summon then they have a true moat that would justify a crazy valuation.
The problem isn't technical, it's cultural / structural. The legacy companies are unlikely to modernize or innovate in a EE/CS HW/SW fashion unless someone lights a fire under them, but as is they are structured to throw together thousands of individual supplier parts and doomed to locally optimize versus Tesla's massive vertical integration.
I agree the problem is hard, but the people that solve the problems share knowledge amongst each other + jump companies routinely... And much of their work is fueled by shared research innovations.
The problem isn't technical, it's cultural / structural. The legacy companies are unlikely to modernize or innovate in a EE/CS HW/SW fashion unless someone lights a fire under them, but as is they are structured to throw together thousands of individual supplier parts
You know Toyota and Hyundai do their own EE/SW and run their own in-house supply chains, right?
The sensor suite in a modern car can basically handle most of that stuff and vehicle controllers can basically already take a full control. How do you think lane assist (must detect road layout), collision warning (detects cars), adaptive cruise control (detects cars, plus control over speed) and auto-park (control over steering and awarness of kerb and other cars) work?
It's just about adding GPS navigation (or rather integrating it) and combining all together, but that is just computer/software.
Tesla's FSD is basically just software and massive dataset for training. The physical stuff is all established technology, nothing special.
Tesla is still light years ahead on actual rich driving data. Not 100% certain that is the key to the castle, but I am guessing they have more driving data than all the other competitors combined.
Yeah. For edge cases that haven’t been simulated yet. Waymo should know. They got stuck in the middle of the street in a blackout. Endangering everyone around, the dumbest self-driving vehicle out there.
🤣😂🤣😂🤣😂🤣😂🤣😂 you forget that legacy auto makers move at the speed of molasses, while Tesla moves at the speed of thought.
Even if the lagacy auto makers agreed to license Nvidia’s self-driving platform, it’d take years to start production. At least 3. Tesla will have scaled by then…
Tesla will? Based on what? They have missed all their own timelines by years already and you still believe in them?
Legacy do stuff first and then talk about it, Tesla talk about stuff and then try to figure out how to deliver it. You seem to live in a world where they actually delivered, well they didnt. Still trying to make a semi and roadster, both already sold but not delivered. Meanwhile others are delivering electric trucks, buses, sports cars.
True, I don’t trust the timelines. It’s more of when, not if. Could be 10 more years and I’m ok with that. They’re doing the impossible. You can’t put a timeline on that. Just like you couldn’t put a timeline on when SpaceX was going to catch a reusable rocket using mechanical arms, perfectly on its FIRST TRY, a world first achievement!!! A still the only company to ever do it. Just like E2E FSD….
Sure, they’ve could’ve stayed on the Waymo way. But it’s not the best long term, 25+ years.
Yeah, Tesla does thing differently. That’s why they get different results. Instead of -$ on the balance sheet they’re +$$$…
Totally anecdotal experience. But using FSD v14.2.2.2 is very safe just mot as smooth as v13 was. But far safer. I don’t remember the last I had a critiacal disengagements. Even when there were close calls. I let FSD take care of it and it evaded problems amazingly when pushed to do it.
Many times it sees issues faster than I do. Specially in the dark. I realize why, after it has done the action already. Park amazing. Into my driveway or parallel parks as well. Makes multiple-point turns to get out of a dead end/tight spot. Pulls out of the parking spot, with no one in the car, then picks me up at my location, eventually lol too pedestrian cautious rn. Curb to curb. I don’t need to touch the wheel at all. I drive 6k miles a month. City to city and no problem.
Roundabouts? Amazing. 4 way stops? Amazing. Cronstruction zones? Unless it’s a street closure, it’s amazing, it definitely needs to read the sign that it’s closed.
Sure it’s not perfectly smooth, yet. There still brake jabs, and sometimes does weird moves but never dangerous maneuvers. Unless it’s an open road it will take more space but there’s no one around. Once v14 gets to v13 level of smoothness it’ll be heaven! But it’s already far safer than the best human driver I’ve ever seen.
Dunno if sarcasm. in 2017, the semi and roadster were unveiled, and i became obsessed w tesla and tried to figure out how to make money from them, maybe get a referral code like i had at elon's x.com. I didn't buy my first share until 2020.
The idea was tesla would move fast and break things, like spacex.
It took lagacy auto 5 years to make a new model, tesla could promise to do that in two years, but now 9 years later, still can't buy a semi or a roadster. what i do like is grok integration.
grok and AI have changed the competition. what it took tesla many years to finally get self driving will not take a copycat that long. whole chinese companies have come and gone while i'm waiting for my semi.
we are still first to fsd, but the moat has evaporated.
when robocab was found too generic to trademark, it only took the other guys 2 weeks to trademark "cybercab" ahead of us.
that's true but also an analogy. we are pretty good at doing the impossible late. so sometimes we aren't first to market even in market segments we created.
When I bought that share of tsla in 2020 I bought a share of ford as a control group. the ford share has doubled. tsla is 15x for my first share, 2x for my average, so i'm happy, but still frustrated.
The roadster is a fun/side project. It not part of the mission that why it’s not on the priority list, which I’m ok with, as an investor as well.
That just means they are trying to improve it because they weren’t happy with how it turned out. They rather take longer to release a great product than rush a bad product that wasn’t up to their standards
I mean he’s said multiple times that Tesla will be the most valuable company in the world…
That’s the same thing. Unless someone can’t use their critical thinking skills. It means they will be making the most money, by bringing the most value to the world. That’s how a company get to being the most valuable company in the world. NVDIA is a perfect example of that. It’s given a lot of value to the world and the world has paid them by making the current most valuable company in the world.
NVDIA is the launch pad. Tesla, Google, Meta and the rest are the rockets.
The BIG money will be in the AI applications. The software that solves real world problems. Chips like NVDIA are key, but the real value is in the software that changes the world. It’ll dwarf chips long term. Like software giants are beating hardware giants. But we’re at the beginning of the new AI age…
There is no similarity between Nvidia and Tesla and how the achieved their market cap. Nvidia earns money, Tesla hardly does it and not even close to justify their valuation. Tesla made their valuation the same way like Theranos, Wirecard, Enron and all other frauds, by lying and cheating.
Not right now, but i said “will be”. So that means in the future…
Of course Tesla stock is at a premium. Has a higher ceiling than NVDA does.
We’ll just have to wait until 2035 to see if Elon gets Tesla to meet the 12 financial tranches, from his new pay for performance package.
Energy and FSD are growing rapidly. And making a higher % of teslas FCF. Then you have the other project, Robotaxi & Optimus. That will take longer to move the needle financially. When they do, they’ll dwarf the current revenue, just like Nvidia’s revenue for AI chips now dwarf their legacy chips.
Of course that’ll take time. Nvidia made the launchpad. Tesla and the rest of the mag7 will be the rockets. Some go higher than others, my bet is on Tesla. But until 2035 we won’t know who went the furthest.
If there’s one thing I’m pretty confident in, these domestic legacy automakers are incapable of getting past their supplier limitations when it comes to executing new systems. Maybe Nvidia becomes one of those suppliers and helps them do it all, but I’m pretty sure they’re busy building architectures, and designing and delivering the chips that run on them.
Then you have the Rivians of the world who probably get it but they want to scale on their own and will thus be limited because their volume and cash.
Then you have the Chinese all going HAM on their own and able to scale. Those are the ones to worry about.
Google and Nvidia are the only companies that will have their hands in all of these products across multiple brands. Teslas valuation is absurd. By current metrics, if Tesla has 100k robotaxis running 400 dollars a day of revenue, the PE of the stock would be approx 80. That's how much of this is priced in already.
SaaS margins will tank as FSD tech improves. How is Tesla going to sell FSD for $10K if some Chinese company sells their own FSD tech for $1K or maybe even makes it free?
Most consumer software and SaaS is a commodity. The costs drop as the technology because widespread and common. FSD prices will drops faster than subscriptions will increase, and it will ultimately become free or near free.
I mean, how much do you pay for cruise control nowadays? What about auto wipers or auto windows? What about navigation? This stuff becomes standard and you can no longer charge for it.
I agree that eventually margins will reduce but Tesla is the best rated autonomy software in china as well. There are some limited geofenced applications by other companies, but it’s not widely applicable so it’s not really the same thing. Besides, China is the outlier and probably ~10 years ahead of most countries in production. If Tesla has 10 years to build out a robotaxi fleet in most countries then it won’t really matter who comes next.
TSLA should be worth between $30 and $50. I saw even ultra-bull ARK investments has no benefit from humanoid robots until 2029 at the earliest. Given massively declining car sales, declining car margins, no active robotaxi service, no humanoid robot potential till probably 2035 or 2040 at best, and new new viable vehicles, TSLA should be tanking. Every other automaker is chipping away at their lead. And for some reason the rideshare business is extremely low margin, but TSLA bulls are counting on it as like 2/3 of their valuation (so over $1T). Yes, TSLA is currently operating at less than 50% capacity at factories, but as the sales continue to drop, they can't just produce vehicles they can't sell to earn 25-cents per mile at a cost of $30,000 + maintenance.
NVIDIA and Google competing for robotaxi. Boston dynamics closing in on humanoid robot. China kicking ass at EVs. Elon busy with midterms and creating a CSAM easy button. Dont like where this is headed for Tesla
I see no evidence that Tesla has slowed on autonomy - 10x param FSD thinking model in the next month or two (I wonder what this means architecturally), cybercab in a few months, AI5 scale-up next year likely with a limited rollout this year.
They won't have nationwide L4 this year, but their metrics in limited areas where they're testing are extremely promising (less than order magnitude delta vs human drivers for accidents with no evidence afaik of the accidents being potentially fatal), and that's ultimately the competitive bar for the next year or two.
AI5 scale-up next year likely with a limited rollout this year.
I'm too lazy to dig up the quote, but Elon's has suggested all AI5 output is going to test articles this year. If true, rollout isn't happening at all until 2027.
Yeah, it’s hard to pin down a timeline, and that’s why the stock is so volatile. It honestly pisses me off they dont publish v14.2 data. If it is so good, they should publish.
Doing my best to estimate:
V12.5 had 300 miles till intervention on the public tracker. But an independent AMCI study (the last one ive seen) had V12.5 at 13 miles. Let’s say tesla self reporting owners are too optimistic, and the independent auditors are too stringent. So Im just going to take optimistically take 75% of the public tracker - which would be about 1,650 for FSD 14.2. There are some oddities like 5% of the entire dataset from british columbia, but I’ll ignore those for now. I think youd find consensus 10,000 is the absolute minimum for robotaxi. Which means we need a 6x improvement from 14.2.
Ashok Ellluswamy said for l4 truly unsupervised, you need human equivalent which is around 670,000. We still need 400x improvement.
Just adding a $100 lidar when you already have huge built in advantages would probably do wonders, but who am I to question Elon. The same lidar was $25,000 when he made his big cameras only declarations
The places with the clearest weather? Where tesla pal alto headquarters and giga texas are (and thus employees and enthusiasts who are encouraged to log good reports)? Where tesla has been optimizing FSD the most (austin)?
Tesla stock price right now assumes Tesla wins everywhere on FSD. It’s not assuming it wins texas and California only.
The rollout for L4 is going to be incremental. If you're looking at where they launch & scale L4, yes it's going to start there, and that's a massive market. Give it a year or two and they'll be in harder areas. That's the most responsible way they can do things, because they will always be X months ahead in performance in easier regions vs harder regions. This is how everyone else's scale-out will work: pilot in a variety of regions, scale in the easy regions.
The main selling point of Teslas approach was that it was a flick of a switch and it works everywhere at once. So you are saying the are doing the geofenced approach Waymo have been doing for years.
Just gonna quote elon himself here : “If you need a geofence area, you don't have real self-driving!”
Tesla's going to have L4 everywhere & is doing a march of 9's in every region. Because we live in reality, some regions are further along that march of 9's than others, they're all progressing at good speeds.
Musk says a lot of things, he's probably referring to hd mapping in your quote.
So far their military robot dog bots look cool. Boston dynamics has been around for what, 15 years? I would expect them to be way ahead and mass producing humanoids by now. It’ll be interesting to see how Tesla’s mass production compares after only ~4 years of development.
No one player can practically speaking ever get too far 'ahead' on something as complex as robotics. All the puzzle pieces need to be in place, and there isn't one single company working on all the puzzle pieces.
Smartphones didn't happen until display tech, chip tech, and communications tech all reached a suitable level for it to happen, but none of the major smartphone players invented any of those technologies. It was just time to put them all together.
Just like with other brands going all in on EV years after Tesla lead the pack. It 'normalises' the field. 15 years or so ago EV's were exotic, now they're mainstream, they are everywhere and you would be surprised if your neighbour bought a new car that is not an EV. Everyone wins, advanced economies see the sale of new fossil cars sunsetting, with reduced oil dependence, air pollution and global warming effect as a result.
Same thing with autonomy, I think. Long a pipe dream, now more and more brands jump on the train and that's a good thing. It will 'normalise' this endeavour. We are not quite there yet, but it's become real and understood and worthy of attention and investment. As a result we'll have less stress, less traffic deaths, less congestion, less cars needed and more liveable less 'car-centric' cities and communities.
From what I gather on X, there are like 40 "robotaxis" in Austin two or three which of are Cybercabs.
And why am I on X? Because Tesla, Tesla AI, and Elon thinks its a great channel to sometimes, perhaps inform about product progress without actually saying anything. FML
As a shareholder ; this is not the reality I have been promised again and again.
Now Nvidia is basically playing the chinese card ; making models cheap. Great, just fucking great.
I don't doubt that Tesla should be concerned about their competition, but be aware that Andrew Hawkins takes every opportunity he can to spill ink that hates on Tesla.
I mean there’s always going to be competition as the market is huge. Tesla alone won’t own the whole market. Good thing is Tesla is in the lead with heaps of experience in manufacturing and software with plenty of FSD capable cars on the road already.
“Competition” has been coming for the past decade and this is probably the only one that could rival FSD. Then again they probably won’t be as profitable as Tesla. Competitors will have to split profits between nvidia.
Spoiler alert: Tesla’s not worried.
It would be unwise for any company to underestimate their competition.
My perspective as a TSLA shareholder is that any relevant comparison between Tesla's FSD and nVidia's autonomous vehicle platform needs:
Based on current information, this community has no idea which system is better, or whether one system is evolving quickly enough that it could outpace the other over time.
Elon Musk has been incorrect, year after year, about FSD achieving true autonomy.
But we cannot take nVidia's limited demo as proof of anything either.
Almost everyone* has been wrong about autonomy year after year. Waymo, Cruise, etc also had wildly optimistic predictions. Nvidia’s chip is cool, but unless you have a fully integrated system and can scale production profitability then it’s basically a really good demo / lab scale, not a product to be produced in the millions. There’s no reason to expect that this will be done any time soon.
Nvidia has a powerful chip to rival Tesla’s.
That’s all. They don’t have fully integrated autonomous systems with years of refinement trained on billions of real world miles. Any company trying to compete with Tesla FSD is permanently 5-10 years behind, at least until true human level AGI emerges.
Precisely, and that's what Cosmos and Drive Sim are for. They worked around the problem entirely. No need for billions of miles when you can do distillations of trillions of miles synthetically. Classic example of disruption.
Waymo did much the same thing with MGAIL, ChauffeurNet, MultiPath, SimulationCity, and Waymax. That's exactly how Waymo has been able to put driverless vehicles on the road already while Tesla is still figuring it out — they found a way to skip past the entire "real world miles" problem.
Even if you could skip all the real world training (doubtful) then you still have to manufacture millions of cars with the right sensor suite… so best case (for competitors) this is an issue for Tesla like ~5 years from now?
Xiaomi delivered 400,000 cars with NVIDIA hardware last year, about half of those being Thor-based YU7s. WeRide and Pony are both already driverless on this same hardware stack as well. And of course, every Mercedes CLA being delivered this year (and soon, every GLC) has the NVIDIA stack too.
Geely's Zeekr has Thor in production as well. So does Li Auto. Volvo's ES90 and EX90 already have an Orin package. Rivan's R1S and R1T do too. Lucid's Air and Gravity also.
So... now. The threat is now. Millions of cars will be manufactured this year with sensor arrays and compute packages equivalent to or better than Tesla's. It is not happening five years from now — it is happening now.
That’s not consistent with the article but okay:
“And by 2028, Nvidia predicts its self-driving tech will be in personally owned autonomous vehicles. Also in 2028, Nvidia plans on supplying systems that can enable Level 3 highway driving”
The company who produces this tech is telling you that optimistically it will start rolling out in 2028…
For L3/L4 consumer-owned vehicles. It's L2 today. Same as Tesla.
People seem to confuse this all the time… just because something is classified as L2 doesn’t mean the capability is the same. Tesla is capable of L4/L5, right now customers with FSD experience L4 (myself included), but for liability Tesla is leaving it as L2 until they want to take the liability (and likely up the subscription cost). There are millions of these Teslas on the road today. The Nvidia equivalent is going to start to roll out in 2028.
This is 100% true. If you know you know.
That's not how SAE J3016 works at all. As always, I really recommend that people actually read is — it's way easier to digest than you think. Crack open a beer, spend an evening skimming through it. There's a lot of interesting material within it. At present, Tesla's FSD is a system with L2 features only, it isn't capable of L4. It may eventually have L4 capabilities, but it doesn't have them now.
Separate from what hardware those cars use, and wyamos use, there are multiple other 'car platforms' (car, software, hardware and sensors and cpus on-car) that are working driverless robotaxis in wide use. Several driverless taxi comapnies in china, waymo has reached 1 million paid rides a week.
Pony.ai is said to have 1k driverless taxis on the road in the 4 major cities of China, per https://techcrunch.com/2025/11/25/chinas-pony-ai-plans-to-triple-global-robotaxi-fleet-by-the-end-of-2026/.
How much differen will new hardware matter? no one knows.
Rivian appears to be switching to their own in-house chip and software.
https://www.youtube.com/watch?v=MCxNk0f9j8U
NVIDIA just put up a video you should watch — it explains exactly what I told you yesterday.
I watched and Tesla made a similar presentation ~5 years ago and did a similar demo ~9 years ago
Yes, that's more or less true. Tesla's doing (or has been trying to do) similar things.
I think you got it backwards. Nvidia is doing what Tesla has been doing… and that’s why this is 5-10 years behind. Full circle 😂
You forgot Waymo’s gigantic geofence and cost-no-object crutches! Accident, or intentionally being disingenuous?
Neither. Tesla, take note, also finally pivoted and has been attempting to trial in constrained geofences.
You seriously believe Tesla choosing to begin service (incredibly wisely) in a small area is equivalent to Waymo relying on LIDAR to precisely geolocate their vehicle in an ultra-high resolution pre-made 3d map of every street, curb, lane line, sign, signal…?
Seriously?
Is a geofence. That's what geofencing is. You begin service in an area that is a known quantity to control for unknowns. You expand that geofence as you become confident that environs outside of the initial geofence are now known.
That's what Tesla is doing.
No, I do not — I don't believe it's equivalent because that not what LIDAR is or how it's used. This has been explained to you repeatedly for like six or seven years now. Lidar geolocation reliance isn't a thing and it never has been — these cars are equipped with GPS and they have been from the start. They don't need some sort of strange elaborate rube-goldberg point-cloud machine to geolocate themselves.
If you think using LIDAR as the primary means to located yourself in the world sounds dumb, that's because it is: You've hallucinated an entire architectural choice that never existed.
What happens if there is a power outage?
And you have been repeatedly wrong for years. Now with AI, it is easy to check. Sorry for the loss of formatting.
—————
Waymo's geolocation system uses LiDAR as a core sensor, combining its data with cameras, radar, GPS, and highly-detailed pre-built maps to achieve centimeter-level accuracy. This multi-sensor fusion allows the Waymo Driver to determine its precise position on the road.
How Waymo Uses LiDAR for Geolocation 3D Environment Mapping: Before a Waymo vehicle operates in a new area, the location is manually driven and mapped using sensor-equipped cars. The LiDAR sensors paint a precise, three-dimensional picture of the surroundings, including permanent features like the height of curbs, lane lines, traffic signs, and buildings. This results in a highly-detailed map that has far more information than standard consumer maps. Real-time Localization: As the autonomous car drives, its onboard computers compare the real-time 3D data from its LiDAR and other sensors with the pre-existing high-definition (HD) maps. By matching the live sensor data to the static map features, the car can pinpoint its location to within 10 centimeters of accuracy. Reduced Reliance on GPS Alone: While GPS is used, the detailed mapping and LiDAR localization mean the vehicle doesn't solely rely on GPS, which can be less accurate or lose signal in urban canyons or tunnels. Focus on Dynamic Objects: By knowing the static environment from the map, the system's sensors and software can focus their processing power more effectively on dynamic, moving objects like other vehicles, pedestrians, and sudden changes like construction zones.
————
This doesn't say what you think it does. Read it again, carefully.
A hypocritical statement, given that Tesla also geofences its Robotaxi service.
Elon Musk himself also stated during the Q1 '25 earnings call that it was possible that Tesla would have to customize its trained software to work better in specific locations:
"It does seem increasingly likely that there will be a localized parameter set perhaps sort of … especially for places that have, say, very snowy weather. Like say if you're in the Northeast or something, like there's … you can think of it, it's kind of a human. You could be a very good driver in California, but are you going to be also a good driver in a blizzard in Manhattan? You're not going to be as good."
Source: https://www.rev.com/transcripts/tesla-q1-2025-earnings-call
If true, this would dampen Tesla's FSD scalability
Haha. Waymo cannot operate outside an area where they have created ultra-high resolution 3d maps of every curb, lane line, signal…
Tesla is merely starting service in a small region before they scale. And customizations to geographic areas to enhance the SW is in a completely different league to only being able to operate in areas where your LIDAR can geolocate you with extreme precision within this pre-created 3-D world. You really should not be investing.
Why in the world are you on a Tesla investors club Forum, if you don’t know, basic information such as this? I’m a firm believer unless you are a complete expert in a company, you should never consider investing. And by complete expert, I mean you have spent thousands of hours of research.
If Tesla has to re-train to get a localized parameter set, how is this fundamentally different than 3D mapping a new area? Both methods require a vehicle or vehicles to drive around the location.
As someone who has been investing since 1997 and retired in 2022, more than 2 decades ahead of schedule, my investing skills are, on the CAGR numbers, far better than the vast majority of both retail and professional money managers.
I've been a TSLA shareholder since 2011, read the SEC filings, and watch the progress of both FSD and facilities construction very closely.
If you don’t understand why adding some custom parameters is different than creating and maintaining a brittle ultra-high definition map, then I can’t help you.
Investing experience does not help with investing in hi-tech companies if you don’t understand the tech.
Many millions of miles of real-world data (maybe billions) is necessary for scaled autonomy.
You were wrong about Tesla reaching autonomy, now you're wrong about this. Quit spreading FUD.
I don't think the real world miles matter. Even Tesla has simulations set up to help train their systems. I doubt they use the messy data from the fleet as much as you think.
Just because they aren’t worried doesn’t mean they are underestimating competition.
Tesla should be. There's many competitors working on these systems without the publicity and ethical issues of testing on public roads.
Tesla's system is flawed and it's unlikely to ever beat a manufacturer who can harness radar and/or lidar in the future
Tesla’s not worried because their CEO doesn’t care and already got paid lol
https://x.com/theevrydaychris/status/2008338591051874449?s=46
$NVDA quietly taking TAM away from $GOOGL (after $AVGO TPUs) and $TSLA (after $AMD).
It's all HYPE!
Says the person who probably doesn't own a car. Let alone one that can drive itself 😂
Teslas not even worried about declining sales and revenue 💀
Well here’s the reality:
Tesla FSD: already production vehicles deployed vision-only end to end neural network model with ~15B parameters trained on 876,000 hours (100 years) of real world data and simulation data in closed loop, scaling up reasoning in v14.3 deployment in Q1 2026. Currently driving ~450M miles per month, currently scaling a robotaxi service with imminent safety supervisor removal.
Nvidia Alpamayo: training framework and teacher model with 10B parameters (not for direct deployment in production vehicles) for variety of sensor suites trained on 1,700 hours of real world training data and a whole lot of simulation data with chain of thought reasoning. Currently deployed on a few test mules and scaling a pilot program in Q1.
Where did you get that parameter count estimate?
In 2022, they had 1 billion parameters. In August 2024 when they rolled out FSD v12.5.1 they increased the parameters by 5x according to release notes and in November 2024 when they released FSD 13.2, they increased parameters by 3x according to release notes.
We don’t know what happened to the parameter count between 2022-2024. It could have gone up or down, but unlikely down since they went end to end neural network in 2024. That’s why 15B is an estimate, likely a conservative one.
2022 was before end-to-end, so that was the total parameter count of all the neural networks. The first end-to-end neural network came out at the beginning of 2024 with v12. We don't know the size of that initial neural network, so we can't use subsequent increases to calculate the current size.
Do you think going end to end more likely shrunk or increased the parameter count?
It's impossible to know. Not all parameters are the same. It's a bit of a junk number anyhow, if you're trying to assess absolute performance.
No idea, honestly. I can see it being smaller because a lot of the old neural networks still need to be running, so there may not have been enough room compute-wise to run all of those and run another neural network equal in size to the previous total at the same time.
That’s some hopium if you think that it is imminent without a safety supervisor. Only thing imminent is a crash when that happens. I have full self driving on HW4. It works amazing 99% of the time until it doesn’t that one time.
Was using it driving back from Virginia Beach this summer, it got confused coming out of a construction zone and went into the shoulder thinking it was a lane bc it was newly painted. Almost drove straight into the railing, it would have split the car.
Some guy posted a video like last week in the Tesla subreddit on just Tesla with fsd blowing a stop sign going 40 mph.
Why do you think your version is the same as Austin robotaxi? They could heavily train just in Austin data and have essentially no edge cases.
Also there are almost no safety issues with 14.2.2.2. Yes inconveniences…or where maybe a remote driver would need to step in. But safety. Not much.
I don't know why people think FSD needs to be perfect to be usable.
Even if it still causes a few deaths every 1 billion miles, it would save many lives and represent a marked improvement over having human drivers who would kill about 15-20 people and injure many more in that same distance.
This thing called weather still exists and Tesla doesn’t have the sensor suite to handle it
Not really as you assume drunk drivers don’t still exist as we transition out of human driven vehicles so being 3 times better than a sober human is not good enough. Probably needs to be 10 times better than human for the market class that currently drives Teslas.
No, I assume drunk FSD doesn't exist (because it doesn't).
Drunk drivers are an inherent and inseparable part of the pool of human drivers, including Tesla drivers (non-FSD). So there is no point in isolating and ignoring those drivers for statistical purposes.
If you were to compare FSD to only the best-of-the-best drivers, you'd also have to exclude:
as if they weren't on the road — which is silly, because we can't prevent them from sharing the road with us.
In fact, those are exactly the drivers we should be moving over to FSD ASAP to make us all much safer.
3x better is already better than vast majority of drivers… whether people realize that or not.
I think they need to deploy 14.3, which will be a step change in how it drives because it will have 10x more parameters in the neural network and reasoning capabilities. Then they need to validate that for a month or two before removing the safety supervisor. All in all, should be around March/April when the Cybercab starts volume production, otherwise those volume produced cybercabs will be sitting in lots since they don’t have steering wheels.
Reasoning capabilities is what exactly?
The end to end neural network, which takes cameras as input, will output reasoning tokens in addition to the controls (steering wheel, acceleration, brake). The reasoning tokens would explain step by step why the car is taking a certain action.
This allows Tesla to better debug why the car makes mistakes when it does, and then train out those mistakes and train out bad reasoning as well, leaving just good driving with good reasoning.
The Austin cars have been automatically taking themselves to problem areas in their geofence to validate training. They'll reach enough safety for unsupervised in that area before they crack everywhere else.
Was that the one with a stop sign on a railway crossing?
You sound like you drank the Kool aid
And its still a L2 system, and the taxi service is still nothing more than Waymo achieved years ago. But, next year I guess?
It’s way less than what Waymo achieved, Waymo is in multiple cities and doesn’t have safety drivers.
What Waymo achieved -years ago-
2 weeks. Trust me.
It will become a L4 system this year, and will likely surpass Waymo on at least some metrics (# of cars, # of rides per week, # of cities, or safety stats) this year also.
If not, then I would agree with you in your skepticism going forward
Today they have a bunch of cars going around with safety drivers but you feel confident that they will make big improvements this year and surpass Waymo in some way. Well I admire your optimism..
The safety drivers are not driving the cars though. People want so badly to see and predict the future ahead of the market and here it is on a silver platter for everyone. Don't let your biases fuck you over.
They are sitting there to kill it when it screws up. Its no different from FSD shown for years. Except this is easier because its a geofenced easy area with good weather conditions. Show me it going coast to coast without a single disengagement, then I be impressed. Make it do it 10000 times in all weather and traffic conditions and I maybe start to think its starting to be ready for a release.
Do you not have access to YouTube? It's littered with examples, especially since December. And it has gone coast to coast 100% FSD. The guy who did it posted his telemetry data and all.
I saw one video of a guy trying, the car crashed in to scrap on the highway under excellent conditions.
And then still occasionally drives through red.
Here's another take, Tesla has zero unsupervised miles driven today, same as NVDA.
Now NVDA makes their own chips and can scale the model to infinity because they are not chip constrained. The teacher pupil model scales better due to lower car hardware requirements, once it's distilled small enough it will run on any production car with any sensor kit. This makes them scale up lightning fast.
Remember, NVDA isn't offering product directly (B2C). The whole idea is to go through partners (B2B) of which they have many.
There are quite a few NVDA partners using NVDA hardware and software stack modules in L4 production with unsupervised miles. Pony is running NVDA hardware and stack, for instance. Nuro... same. WeRide for another. All of these companies have unsupervised driverless miles. So what you're saying is not true.
Pony, Nuro, and WeRide do not use NVDA planning stack lmao.
That's a doozy of a sentence. Nvidia Drive is an entire platform ecosystem, it isn't just a planning module. There's hardware, software, sample architectures and algorithms, cloud services, a partner tier system, and like ten other levels. It isn't a binary opt-in-opt-out, nor is it contained to a single corner of the stack or implementation. It's more like a framework.
And I can guarantee you it is not an integral part of these companies software stack
You didn't even know what NVIDIA Drive was a moment ago. It's okay to be out of your depth, but repeatedly bluffing and blustering through the conversation isn't a good look.
Yes, these companies all use NVIDIA as an integral part of their software stack, both training-side and inference-side. That's what DriveOS is. Again, this is an ecosystem. You pick and choose what you want from it, and there are many, many different levels of involvement. At the fundamental, most basic level, nearly all the industry players are using some NVIDIA SDKs/APIs and hardware/software implementations as an integral part of their systems — that's how it's been for years.
Bud, I am an ML engineer at one of these 3 companies and we dont use any of this 😭😭😭
You're insufferable the way you talk btw
That's cute.
Try bullshitting someone else, champ. As I said before — repeatedly bluffing and blustering your way through this conversation isn't a good look, and it isn't going to work.
Tesla is also going to be doing teacher pupil models too if they aren’t already. They have to for the scaled down version of FSD v14 for HW3 vehicles in Q2 of this year.
I would not let my Tesla drive autonomously. Only 1 yr old and it makes the most dangerous decisions even in broad daylight (where lack of lidar wouldn’t even matter).
Anything Andrew J. Hawkins writes goes straight to the trash.
As soon as I saw the title, I knew it was him lol
A look at his other headlines makes it clear what agenda he's pushing. Journalists shouldn't be pushing any agenda, to be clear, but man is he transparent.
Title is copy+pasted from the article, I figure it'll rub some people on the sub the wrong way but I'm following Rule 4.
I personally don't find NV's competition concerning given Tesla's ability to scale - my belief for a decade has always been that every software company would hit L4 within the span of a year or two - this is how the entire history of software has gone, and we've seen the same with AI across the industry... So the limiting factor becomes # cars produced which Tesla can excel at. Full disclosure I'm pretty heavy on TSLA NVDA and GOOG stock though I'm not really invested for NV's autonomy or Waymo. AI is going to take off and there will be many winners, IMO whoever has talent and a path to $ will win.
All it takes for NVidia to sell/partner to one of heavy hitters like GM, Ford, Stellantis or Volkswagen and... Boom , scale that dwarfs even Tesla.
Have any of them demonstrated over the air updates? It isn't just the computer but all vehicle controllers that need to integrate including camera variants and positions.
Trivial problem.
I think OP undersells how hard building the software is that can handle proper L4, and oversells how copy able it will be. But I agree that we won't see one company standing alone with L4 for very long, so I agree that in and off itself can't be why you value a company highly.
If Tesla has any shot of living up to the valuation it will need to trigger Elon's pay package then the play is around the fleet and in particular charging. No other competitor has a charging network of their own design. If Tesla can automate charging alongside robotaxi, L4 and long range banish/summon then they have a true moat that would justify a crazy valuation.
The problem isn't technical, it's cultural / structural. The legacy companies are unlikely to modernize or innovate in a EE/CS HW/SW fashion unless someone lights a fire under them, but as is they are structured to throw together thousands of individual supplier parts and doomed to locally optimize versus Tesla's massive vertical integration.
I agree the problem is hard, but the people that solve the problems share knowledge amongst each other + jump companies routinely... And much of their work is fueled by shared research innovations.
You know Toyota and Hyundai do their own EE/SW and run their own in-house supply chains, right?
I was speaking of the Western companies Bwunt referred to
But it is just the computer.
The sensor suite in a modern car can basically handle most of that stuff and vehicle controllers can basically already take a full control. How do you think lane assist (must detect road layout), collision warning (detects cars), adaptive cruise control (detects cars, plus control over speed) and auto-park (control over steering and awarness of kerb and other cars) work?
It's just about adding GPS navigation (or rather integrating it) and combining all together, but that is just computer/software.
Tesla's FSD is basically just software and massive dataset for training. The physical stuff is all established technology, nothing special.
Cars will self-drive to the dealerships when updates are needed, easy peasy!
Tesla is still light years ahead on actual rich driving data. Not 100% certain that is the key to the castle, but I am guessing they have more driving data than all the other competitors combined.
Did you need billions of miles of training data to drive safely?
Question is, do they need so much of it. It's a good way to train certain models, absolutely, but the question is, are they really necessary.
Yeah. For edge cases that haven’t been simulated yet. Waymo should know. They got stuck in the middle of the street in a blackout. Endangering everyone around, the dumbest self-driving vehicle out there.
https://nvidianews.nvidia.com/news/general-motors-and-nvidia-collaborate-on-ai-for-next-generation-vehicle-experience-and-manufacturing
https://nvidianews.nvidia.com/news/toyota-aurora-continental-nvidia-drive
🤣😂🤣😂🤣😂🤣😂🤣😂 you forget that legacy auto makers move at the speed of molasses, while Tesla moves at the speed of thought.
Even if the lagacy auto makers agreed to license Nvidia’s self-driving platform, it’d take years to start production. At least 3. Tesla will have scaled by then…
Tesla will? Based on what? They have missed all their own timelines by years already and you still believe in them?
Legacy do stuff first and then talk about it, Tesla talk about stuff and then try to figure out how to deliver it. You seem to live in a world where they actually delivered, well they didnt. Still trying to make a semi and roadster, both already sold but not delivered. Meanwhile others are delivering electric trucks, buses, sports cars.
True, I don’t trust the timelines. It’s more of when, not if. Could be 10 more years and I’m ok with that. They’re doing the impossible. You can’t put a timeline on that. Just like you couldn’t put a timeline on when SpaceX was going to catch a reusable rocket using mechanical arms, perfectly on its FIRST TRY, a world first achievement!!! A still the only company to ever do it. Just like E2E FSD….
Sure, they’ve could’ve stayed on the Waymo way. But it’s not the best long term, 25+ years.
Yeah, Tesla does thing differently. That’s why they get different results. Instead of -$ on the balance sheet they’re +$$$…
Totally anecdotal experience. But using FSD v14.2.2.2 is very safe just mot as smooth as v13 was. But far safer. I don’t remember the last I had a critiacal disengagements. Even when there were close calls. I let FSD take care of it and it evaded problems amazingly when pushed to do it.
Many times it sees issues faster than I do. Specially in the dark. I realize why, after it has done the action already. Park amazing. Into my driveway or parallel parks as well. Makes multiple-point turns to get out of a dead end/tight spot. Pulls out of the parking spot, with no one in the car, then picks me up at my location, eventually lol too pedestrian cautious rn. Curb to curb. I don’t need to touch the wheel at all. I drive 6k miles a month. City to city and no problem.
Roundabouts? Amazing. 4 way stops? Amazing. Cronstruction zones? Unless it’s a street closure, it’s amazing, it definitely needs to read the sign that it’s closed.
Sure it’s not perfectly smooth, yet. There still brake jabs, and sometimes does weird moves but never dangerous maneuvers. Unless it’s an open road it will take more space but there’s no one around. Once v14 gets to v13 level of smoothness it’ll be heaven! But it’s already far safer than the best human driver I’ve ever seen.
Dunno if sarcasm. in 2017, the semi and roadster were unveiled, and i became obsessed w tesla and tried to figure out how to make money from them, maybe get a referral code like i had at elon's x.com. I didn't buy my first share until 2020.
The idea was tesla would move fast and break things, like spacex. It took lagacy auto 5 years to make a new model, tesla could promise to do that in two years, but now 9 years later, still can't buy a semi or a roadster. what i do like is grok integration.
grok and AI have changed the competition. what it took tesla many years to finally get self driving will not take a copycat that long. whole chinese companies have come and gone while i'm waiting for my semi.
we are still first to fsd, but the moat has evaporated. when robocab was found too generic to trademark, it only took the other guys 2 weeks to trademark "cybercab" ahead of us.
that's true but also an analogy. we are pretty good at doing the impossible late. so sometimes we aren't first to market even in market segments we created. When I bought that share of tsla in 2020 I bought a share of ford as a control group. the ford share has doubled. tsla is 15x for my first share, 2x for my average, so i'm happy, but still frustrated.
The roadster is a fun/side project. It not part of the mission that why it’s not on the priority list, which I’m ok with, as an investor as well.
That just means they are trying to improve it because they weren’t happy with how it turned out. They rather take longer to release a great product than rush a bad product that wasn’t up to their standards
You missed the part when Elon changed the mission to milk as much money out of the cow as possible before people realise its a dead goat..
I mean he’s said multiple times that Tesla will be the most valuable company in the world…
That’s the same thing. Unless someone can’t use their critical thinking skills. It means they will be making the most money, by bringing the most value to the world. That’s how a company get to being the most valuable company in the world. NVDIA is a perfect example of that. It’s given a lot of value to the world and the world has paid them by making the current most valuable company in the world.
NVDIA is the launch pad. Tesla, Google, Meta and the rest are the rockets.
The BIG money will be in the AI applications. The software that solves real world problems. Chips like NVDIA are key, but the real value is in the software that changes the world. It’ll dwarf chips long term. Like software giants are beating hardware giants. But we’re at the beginning of the new AI age…
There is no similarity between Nvidia and Tesla and how the achieved their market cap. Nvidia earns money, Tesla hardly does it and not even close to justify their valuation. Tesla made their valuation the same way like Theranos, Wirecard, Enron and all other frauds, by lying and cheating.
Not right now, but i said “will be”. So that means in the future…
Of course Tesla stock is at a premium. Has a higher ceiling than NVDA does.
We’ll just have to wait until 2035 to see if Elon gets Tesla to meet the 12 financial tranches, from his new pay for performance package.
Energy and FSD are growing rapidly. And making a higher % of teslas FCF. Then you have the other project, Robotaxi & Optimus. That will take longer to move the needle financially. When they do, they’ll dwarf the current revenue, just like Nvidia’s revenue for AI chips now dwarf their legacy chips.
Of course that’ll take time. Nvidia made the launchpad. Tesla and the rest of the mag7 will be the rockets. Some go higher than others, my bet is on Tesla. But until 2035 we won’t know who went the furthest.
Nobody else can make a vehicle at the low cost and speed like cybercab. So...math
Yeah...
Press X to doubt
Seeing as most of those companies have exited the small vehicle market…
What companies?
If there’s one thing I’m pretty confident in, these domestic legacy automakers are incapable of getting past their supplier limitations when it comes to executing new systems. Maybe Nvidia becomes one of those suppliers and helps them do it all, but I’m pretty sure they’re busy building architectures, and designing and delivering the chips that run on them.
Then you have the Rivians of the world who probably get it but they want to scale on their own and will thus be limited because their volume and cash.
Then you have the Chinese all going HAM on their own and able to scale. Those are the ones to worry about.
GM, Ford, Stellantis and Volkswagen will be unstoppable once they get their hands on Nvidia. Time to sell your stocks, TSLA shareholders 😂
Google and Nvidia are the only companies that will have their hands in all of these products across multiple brands. Teslas valuation is absurd. By current metrics, if Tesla has 100k robotaxis running 400 dollars a day of revenue, the PE of the stock would be approx 80. That's how much of this is priced in already.
You’re ignoring continued growth in Energy, scale up of Tesla Semi this year, and SAAS profit from FSD uptake increasing.
SaaS margins will tank as FSD tech improves. How is Tesla going to sell FSD for $10K if some Chinese company sells their own FSD tech for $1K or maybe even makes it free?
Most consumer software and SaaS is a commodity. The costs drop as the technology because widespread and common. FSD prices will drops faster than subscriptions will increase, and it will ultimately become free or near free.
I mean, how much do you pay for cruise control nowadays? What about auto wipers or auto windows? What about navigation? This stuff becomes standard and you can no longer charge for it.
I agree that eventually margins will reduce but Tesla is the best rated autonomy software in china as well. There are some limited geofenced applications by other companies, but it’s not widely applicable so it’s not really the same thing. Besides, China is the outlier and probably ~10 years ahead of most countries in production. If Tesla has 10 years to build out a robotaxi fleet in most countries then it won’t really matter who comes next.
TSLA should be worth between $30 and $50. I saw even ultra-bull ARK investments has no benefit from humanoid robots until 2029 at the earliest. Given massively declining car sales, declining car margins, no active robotaxi service, no humanoid robot potential till probably 2035 or 2040 at best, and new new viable vehicles, TSLA should be tanking. Every other automaker is chipping away at their lead. And for some reason the rideshare business is extremely low margin, but TSLA bulls are counting on it as like 2/3 of their valuation (so over $1T). Yes, TSLA is currently operating at less than 50% capacity at factories, but as the sales continue to drop, they can't just produce vehicles they can't sell to earn 25-cents per mile at a cost of $30,000 + maintenance.
NVIDIA and Google competing for robotaxi. Boston dynamics closing in on humanoid robot. China kicking ass at EVs. Elon busy with midterms and creating a CSAM easy button. Dont like where this is headed for Tesla
I see no evidence that Tesla has slowed on autonomy - 10x param FSD thinking model in the next month or two (I wonder what this means architecturally), cybercab in a few months, AI5 scale-up next year likely with a limited rollout this year.
They won't have nationwide L4 this year, but their metrics in limited areas where they're testing are extremely promising (less than order magnitude delta vs human drivers for accidents with no evidence afaik of the accidents being potentially fatal), and that's ultimately the competitive bar for the next year or two.
💯 14.2.x is incredible and that's without the 10x param increase
I'm too lazy to dig up the quote, but Elon's has suggested all AI5 output is going to test articles this year. If true, rollout isn't happening at all until 2027.
i believe elon said testing in 2026 and full production by mid 2027.
-source
Yeah, it’s hard to pin down a timeline, and that’s why the stock is so volatile. It honestly pisses me off they dont publish v14.2 data. If it is so good, they should publish.
Doing my best to estimate: V12.5 had 300 miles till intervention on the public tracker. But an independent AMCI study (the last one ive seen) had V12.5 at 13 miles. Let’s say tesla self reporting owners are too optimistic, and the independent auditors are too stringent. So Im just going to take optimistically take 75% of the public tracker - which would be about 1,650 for FSD 14.2. There are some oddities like 5% of the entire dataset from british columbia, but I’ll ignore those for now. I think youd find consensus 10,000 is the absolute minimum for robotaxi. Which means we need a 6x improvement from 14.2.
Ashok Ellluswamy said for l4 truly unsupervised, you need human equivalent which is around 670,000. We still need 400x improvement.
Just adding a $100 lidar when you already have huge built in advantages would probably do wonders, but who am I to question Elon. The same lidar was $25,000 when he made his big cameras only declarations
You need to narrow the data you're looking at to regions Tesla would launch L4 in like California and Texas.
The places with the clearest weather? Where tesla pal alto headquarters and giga texas are (and thus employees and enthusiasts who are encouraged to log good reports)? Where tesla has been optimizing FSD the most (austin)?
Tesla stock price right now assumes Tesla wins everywhere on FSD. It’s not assuming it wins texas and California only.
The rollout for L4 is going to be incremental. If you're looking at where they launch & scale L4, yes it's going to start there, and that's a massive market. Give it a year or two and they'll be in harder areas. That's the most responsible way they can do things, because they will always be X months ahead in performance in easier regions vs harder regions. This is how everyone else's scale-out will work: pilot in a variety of regions, scale in the easy regions.
The main selling point of Teslas approach was that it was a flick of a switch and it works everywhere at once. So you are saying the are doing the geofenced approach Waymo have been doing for years.
Just gonna quote elon himself here : “If you need a geofence area, you don't have real self-driving!”
Tesla's going to have L4 everywhere & is doing a march of 9's in every region. Because we live in reality, some regions are further along that march of 9's than others, they're all progressing at good speeds.
Musk says a lot of things, he's probably referring to hd mapping in your quote.
So it’s the engineers of the other companies that matter. Even with NVIDIAs CEO constantly doing press.
But a story about Elon and the mid terms pops up and that means Tesla isn’t doing anything. Brilliant.
LG showing off a human-form robot today too. Plus, of course, all the Chinese players in that business. And Toyota in with Boston Dynamics as well.
So far their military robot dog bots look cool. Boston dynamics has been around for what, 15 years? I would expect them to be way ahead and mass producing humanoids by now. It’ll be interesting to see how Tesla’s mass production compares after only ~4 years of development.
See: Technological convergence.
No one player can practically speaking ever get too far 'ahead' on something as complex as robotics. All the puzzle pieces need to be in place, and there isn't one single company working on all the puzzle pieces.
Smartphones didn't happen until display tech, chip tech, and communications tech all reached a suitable level for it to happen, but none of the major smartphone players invented any of those technologies. It was just time to put them all together.
Are you a teslainvestor?
I think it's a good thing overall.
Just like with other brands going all in on EV years after Tesla lead the pack. It 'normalises' the field. 15 years or so ago EV's were exotic, now they're mainstream, they are everywhere and you would be surprised if your neighbour bought a new car that is not an EV. Everyone wins, advanced economies see the sale of new fossil cars sunsetting, with reduced oil dependence, air pollution and global warming effect as a result.
Same thing with autonomy, I think. Long a pipe dream, now more and more brands jump on the train and that's a good thing. It will 'normalise' this endeavour. We are not quite there yet, but it's become real and understood and worthy of attention and investment. As a result we'll have less stress, less traffic deaths, less congestion, less cars needed and more liveable less 'car-centric' cities and communities.
I would be worried if people are not doing what Tesla is doing. Robots , Autonomous V, and AI.
From what I gather on X, there are like 40 "robotaxis" in Austin two or three which of are Cybercabs.
And why am I on X? Because Tesla, Tesla AI, and Elon thinks its a great channel to sometimes, perhaps inform about product progress without actually saying anything. FML
As a shareholder ; this is not the reality I have been promised again and again.
Now Nvidia is basically playing the chinese card ; making models cheap. Great, just fucking great.
Not great.
How are they making the models cheap?
By open-weighting them.
open source
In 2026, Nvidia makes nothing cheap.
Also, X and Reddit both have the same caveats, no need to virtue signal either direction.
Just own both stocks, problem solved!
I don't doubt that Tesla should be concerned about their competition, but be aware that Andrew Hawkins takes every opportunity he can to spill ink that hates on Tesla.
nvidia is just trying to sell chips. They make the framework so other companies can use it to make product.
TSLA is currently completely reliant on NVDA architecture for AI training. A win for them is a win for TSLA.
I mean there’s always going to be competition as the market is huge. Tesla alone won’t own the whole market. Good thing is Tesla is in the lead with heaps of experience in manufacturing and software with plenty of FSD capable cars on the road already.
“Competition” has been coming for the past decade and this is probably the only one that could rival FSD. Then again they probably won’t be as profitable as Tesla. Competitors will have to split profits between nvidia.