“Nvidia doesn’t build self-driving cars. We build the full stack so others can,” Huang said, explaining that Nvidia provides separate systems for training, simulation, and in-vehicle computing, all supported by shared software.
He added that customers can adopt as much or as little of the platform as they need, noting that Nvidia works across the industry, including with Tesla on training systems and companies like Waymo, XPeng, and Nuro on vehicle computing.
You're being asked to read between the lines here on something a lot of people have pointed out in various threads: Tesla is an NVIDIA customer, using bits and pieces of NVIDIA's stack. Whether or not Jensen likes FSD (and he probably does!), he's viewing them through that provider-client lens — one client of many, no less. He's not going to step out of line and piss off Tesla, nor is he going to step out of line and piss off his other customers.
These kinds of questions aren't really ever going to get useful thoughts out of him (in either direction!) for that reason. It is what it is.
IDK... Ironically Alpamayo required radar (and includes lidar) inputs to function and Nvidia's own platform requires radar and lidar input along with cameras... I dont think Nvidia allows customers to use the NVidia stack without the required inputs, but who knows.
Tesla doesn't write the middleware and firmware layers themselves, that's all from NVIDIA. Development and infrastructure tooling is all NVIDIA. That's literally the whole point of buying NVIDIA. Otherwise everyone would just buy AMD. The value add NVIDIA provides is software.
Nvidia is the ARM/TSMC/FreeBSD (B2B), Tesla is Apple/Foxconn (B2C). They are the final complete integrated product with global distribution, support infra, and brand name. The companies closer to the final customer makes the most profits and capture the most kind share. *Despite its CEO’s personal holy war against legacy tribal leaders.
Haahahahaahhahahah…. NVIDIA has profit margins of like 60% and 80% on the product and still a lot of people/companies buy them second market for more $… Literally the worst example you could give…. Car companies have horrible margins. I doubt car companies will manage to easily make more than NVIDIA per car even if NVIDIA charges them 3% of car value. Plus NVIDIA captures all the car market or most of it with this…
And it’s a bad analogy. Tesla will ALSO make 80% on the $5k AI part of $50k cars in addition to the 10% on the other $45k. Therefore Tesla does $4.5k better per car.
Irrelevant. It’s the number of cars sold. Not the number of brands. And if Tesla’s system is superior, then they will outsell the vehicles using NVIDIA. They will certainly out profit NVIDIA. Just like iPhone generates more profit than all other brands combined.
Tesla runs inference on their own custom silicon, completely bypassing Nvidia software in the car. They only use Nvidia and CUDA for training because their own Dojo hardware fell short. CUDA is just the 'classroom', once the model learns, it leaves the Nvidia ecosystem and is ported to Tesla’s proprietary hardware to actually drive.
For this reason Tesla can deliver a vision only solution and Nvidia may not be able to.
I'm genuinely not sure what needs explaining here, but I'll give it a shot:
Tesla's "proprietary hardware" does the same inference work as every other inference hardware on the market. It's a bunch of licensed Samsung/ARM IP slapped together with an ASIC in the same way as every other board in existence. Suggesting it is uniquely special in some way because it is 'proprietary' misses the reality of the situation by like a million miles. Compute is (more or less) compute. They didn't invent a whole new way of thinking about numbers or anything.
In actual fact, HW4 (~150TOPS) is at a huge disadvantage to the state of the art (~2000TOPS), which is why the long delay before we'll see HW5 is so concerning to me. The Cortex-A72 CPU architecture on HW3/HW4 is so old (~2015) it literally pre-dates the invention of transformer networks.
What is your point or are you just arguing just to be argumentative?
My point is that Nvidia simply provides the training infrastructure (hardware and software), while Tesla designs the models and handles all inference. Nvidia is just the platform provider; their chips are agnostic. The hardware doesn't care if it's training a self-driving car, an LLM, or folding proteins; it just supplies the raw compute power for whatever Tesla builds.
If you've already forgotten, your claim was that proprietary hardware is "....[the] reason Tesla can deliver a vision only solution and Nvidia may not be able to."
The agnostic characteristics you're now describing do not bolster your original argument, they discredit them. The training platform is the same, and the inference hardware is fungible. The fundamentals are identical. The only difference is the trained model itself.
Nvidia engineer in the backseat from one of the YouTube influencer video confirmed cameras and radar can only achieve L2, same as FSD supervised.
Humanless L4 cannot be enabled without LiDAR for their system. So it is the same as Waymo and everyone else except for Tesla soon to be FSD unsupervised.
You're being asked to read between the lines here on something a lot of people have pointed out in various threads: Tesla is an NVIDIA customer, using bits and pieces of NVIDIA's stack. Whether or not Jensen likes FSD (and he probably does!), he's viewing them through that provider-client lens — one client of many, no less. He's not going to step out of line and piss off Tesla, nor is he going to step out of line and piss off his other customers.
These kinds of questions aren't really ever going to get useful thoughts out of him (in either direction!) for that reason. It is what it is.
IDK... Ironically Alpamayo required radar (and includes lidar) inputs to function and Nvidia's own platform requires radar and lidar input along with cameras... I dont think Nvidia allows customers to use the NVidia stack without the required inputs, but who knows.
Alpamayo is a VLA. Its inputs are an RGB image, text, and XYZ ego history.
He stated himself that he thinks FSD is the most advanced system there is right now.
What? They build hardware and Tesla does everything else. That isn’t bits and pieces of NVIDIAs stack.
Tesla doesn't write the middleware and firmware layers themselves, that's all from NVIDIA. Development and infrastructure tooling is all NVIDIA. That's literally the whole point of buying NVIDIA. Otherwise everyone would just buy AMD. The value add NVIDIA provides is software.
Nvidia is the ARM/TSMC/FreeBSD (B2B), Tesla is Apple/Foxconn (B2C). They are the final complete integrated product with global distribution, support infra, and brand name. The companies closer to the final customer makes the most profits and capture the most kind share. *Despite its CEO’s personal holy war against legacy tribal leaders.
Foxconn is B2B. FreeBSD isn't even a business at all, so I'm not sure what you're thinking there.
You are right about the error in the details, but it’s blinding you to the high level point I’m making.
I added Foxconn after the fact, because unlike Apple, Tesla even manufactures most of the product.
FreeBSD isn’t a business, but it didn’t stop Apple from extracting the value of opensource software to make their products more valuable to the user.
Nvidia is tooling, Tesla is new useful AI appliances. The later has much larger margin potential.
Just use Samsung for your analogy. You're straining it too much as-is.
Haahahahaahhahahah…. NVIDIA has profit margins of like 60% and 80% on the product and still a lot of people/companies buy them second market for more $… Literally the worst example you could give…. Car companies have horrible margins. I doubt car companies will manage to easily make more than NVIDIA per car even if NVIDIA charges them 3% of car value. Plus NVIDIA captures all the car market or most of it with this…
We’re discussing cars. NVIDIA will only garner SOME of the profit in each car sold with their HW. Tesla will garner nearly all of the profit.
Making 10% on 50k is not that better than making 80% on 5k. Especially when NVIDIA will make money on all cars
Basic math. It is actually $1k better!
I love it when people prove themselves wrong!
And it’s a bad analogy. Tesla will ALSO make 80% on the $5k AI part of $50k cars in addition to the 10% on the other $45k. Therefore Tesla does $4.5k better per car.
Sure mate. Now put in perspective that NVIDIA will work with 30 other car brands….
Irrelevant. It’s the number of cars sold. Not the number of brands. And if Tesla’s system is superior, then they will outsell the vehicles using NVIDIA. They will certainly out profit NVIDIA. Just like iPhone generates more profit than all other brands combined.
Tesla runs inference on their own custom silicon, completely bypassing Nvidia software in the car. They only use Nvidia and CUDA for training because their own Dojo hardware fell short. CUDA is just the 'classroom', once the model learns, it leaves the Nvidia ecosystem and is ported to Tesla’s proprietary hardware to actually drive.
For this reason Tesla can deliver a vision only solution and Nvidia may not be able to.
In other words: They're using the NVIDIA stack. You're not saying what you think you're saying here, you just don't realize it.
That's absolutely not even remotely close to what that means.
Explain.
I'm genuinely not sure what needs explaining here, but I'll give it a shot:
Tesla's "proprietary hardware" does the same inference work as every other inference hardware on the market. It's a bunch of licensed Samsung/ARM IP slapped together with an ASIC in the same way as every other board in existence. Suggesting it is uniquely special in some way because it is 'proprietary' misses the reality of the situation by like a million miles. Compute is (more or less) compute. They didn't invent a whole new way of thinking about numbers or anything.
In actual fact, HW4 (~150TOPS) is at a huge disadvantage to the state of the art (~2000TOPS), which is why the long delay before we'll see HW5 is so concerning to me. The Cortex-A72 CPU architecture on HW3/HW4 is so old (~2015) it literally pre-dates the invention of transformer networks.
What is your point or are you just arguing just to be argumentative?
My point is that Nvidia simply provides the training infrastructure (hardware and software), while Tesla designs the models and handles all inference. Nvidia is just the platform provider; their chips are agnostic. The hardware doesn't care if it's training a self-driving car, an LLM, or folding proteins; it just supplies the raw compute power for whatever Tesla builds.
If you've already forgotten, your claim was that proprietary hardware is "....[the] reason Tesla can deliver a vision only solution and Nvidia may not be able to."
The agnostic characteristics you're now describing do not bolster your original argument, they discredit them. The training platform is the same, and the inference hardware is fungible. The fundamentals are identical. The only difference is the trained model itself.
Mayo
Nvidia engineer in the backseat from one of the YouTube influencer video confirmed cameras and radar can only achieve L2, same as FSD supervised.
Humanless L4 cannot be enabled without LiDAR for their system. So it is the same as Waymo and everyone else except for Tesla soon to be FSD unsupervised.
Nothing is confirmed. It's the engineer's professional opinion.
VP of engineering at Nvidia said the same as this engineer.
They may be right, but they can't confirm anything outside of their own projects.
Cool, he hasn’t been working on this as long as Tesla has
It’s his opinion and Tesla has been working on this much longer than they have
🤣 absence of evidence, is not prove it’s impossible 😂
Just not yet.
Can you prove aliens don’t exist?
One is vaporware and one is being proven out on the roads daily.
At level 2, with a high crash rate and an inadequate sensor suite.
1/7th the crash rate as humans is high now. Good analysis.