At the 2025 Consumer Electronics Show, Nvidia showed off its new consumer graphics cards, home-scale compute machines, and commercial AI offerings. One of these offerings included the new Nvidia Cosmos training system.
Nvidia is a close partner of Tesla - in fact, they produce and supply the GPUs that Tesla uses to train FSD - the H100s and soon-to-be H200s, located at the new Cortex Supercomputing Cluster at Giga Texas. Nvidia will also challenge Tesla’s lead in developing and deploying synthetic training data for an autonomous driving system - something Tesla is already doing.
However, this is far more important for other manufacturers. We’re going to take a look at what Nvidia is offering and how it compares to what Tesla is already doing. We’ve done a few deep dives into how Tesla’s FSD works, how Tesla streamlines FSD, and, more recently, how they optimize FSD. If you want to get familiar with a bit of the lingo and the background knowledge, we recommend reading those articles before continuing, but we’ll do our best to explain how all this synthetic data works.
Nvidia Cosmos
Nvidia’s Cosmos is a generative AI model created to accelerate the development of physical AI systems, including robots and autonomous vehicles. Remember - Tesla’s FSD is also the same software that powers their humanoid robot, Optimus. Nvidia is aiming to tackle physical, real-world deployments of AI anywhere from your home, your street, or your workplace, just like Tesla.
Cosmos is a physics-aware engine that learns from real-world video and builds simulated video inputs. It tokenizes data to help AI systems learn quicker, all based on the video that is input into the system. Sound familiar? That’s exactly how FSD learns as well.
Cosmos also has the capability to do sensor-fused simulations. That means it can take multiple input sources - video, LiDAR, audio, or whatever else the user intends, and fuse them together into a single-world simulation for your AI model to learn from. This helps train, test, and validate autonomous vehicle behavior in a safe, synthetic format while also providing a massive breadth of data.
Data Scaling
Of course, Cosmos itself still requires video input - the more video you feed it, the more simulations it can generate and run. Data scaling is a necessity for AI applications, as you’ll need to feed it an infinite amount of data to build an infinite amount of scenarios for it to train itself on.
Synthetic data also has a problem - is it real? Can it predict real-world situations? In early 2024, Elon Musk commented on this problem, noting that data scales infinitely both in the real world and in simulated data. A better way to gather testing data is through real-world data. After all, no AI can predict the real world just yet - in fact, that’s an excellent quantum computing problem that the brightest minds are working on.
Yun-Ta Tsai, an engineer at Tesla’s AI team, also mentioned that writing code or generating scenarios doesn’t cover what even the wildest AI hallucinations might come up with. There are lots of optical phenomena and real-world situations that don’t necessarily make sense in the rigid training sets that AI would develop, so real-world data is absolutely essential to build a system that can actually train a useful real-world AI.
Tesla has billions of miles of real-world video that can be used for training, according to Tesla’s Social Media Team Lead Viv. This much data is essential because even today, FSD encounters “edge cases” that can confuse it, slow it down, or render it incapable of continuing, throwing up the dreaded red hands telling the user to take over.
Cosmos was trained on approximately 20 million hours of footage, including human activities like walking and manipulating objects. On the other hand, Tesla’s fleet gathers approximately 2,380 recorded minutes of real-world video per minute. Every 140 hours - just shy of 6 days - Tesla’s fleet gathers 20 million hours of footage. That was a little bit of back-of-the-napkin math, calculated at 60 mph as the average speed.
Generative Worlds
Both Tesla’s FSD and Nvidia’s Cosmos can generate highly realistic, physics-based worlds. These worlds are life-like environments and simulate the movement of people and traffic and the real-life position of obstacles and objects, including curbs, fences, buildings, and other objects.
Tesla uses a combination of real-world data and synthetic data, but the combination of data is heavily weighted to real-world data. Meanwhile, companies who use Cosmos will be weighting their data heavily towards synthetically created situations, drastically limiting what kind of cases they may see in their training datasets.
As such, while generative worlds may be useful to validate an AI quickly, we would argue that these worlds aren’t as useful as real-world data to do the training of an AI.
Overall, Cosmos is an exciting step - others are clearly following in Tesla’s footsteps, but they’re extremely far behind in real-world data. Tesla has built a massive first-mover advantage in AI and autonomy, and others are now playing catch-up.
We’re excited to see how Tesla’s future deployment of its Dojo Supercomputer for Data Labelling adds to its pre-existing lead, and how Cortex will be able to expand, as well as what competitors are going to be bringing to the table. After all, competition breeds innovation - and that’s how Tesla innovated in the EV space to begin with.
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Tesla has been working on FSD Unsupervised for quite a while—the hands-off, eyes-off version of FSD. That’ll be the same version of FSD that can get you from Point A to Point B without any user intervention and no requirement for keeping your eyes on the road or your hands on the wheel.
June 2025 is Tesla’s date for the next step in vehicle autonomy and the public introduction of Unsupervised FSD - which was announced at Tesla’s Q4 2024 Earnings Call - so let’s take a closer look at what’s coming.
Launch Date for Robotaxi Fleet
Tesla’s launch of Unsupervised FSD will be in Austin, Texas, but it’ll be limited to its Robotaxi fleet. Vehicle owners won’t be able to access Unsupervised FSD themselves or join the autonomous fleet initially. Tesla announced that its launch in Austin would be for a paid Robotaxi service, much like Waymo’s. Tesla will use it to refine the Robotaxi experience and Unsupervised FSD.
They’ll be working on the whole experience - start to finish - from summoning the robotaxi from the app, to how it arrives, how your trip progresses, where it drops you off, and how you pay. That’s an extensive set of systems - some of which may already be in place, as we’ve seen through Tesla’s Robotaxi app mock-ups.
Tesla is taking strict control of the initial deployments of FSD Unsupervised - and for good reason. A single minor incident or accident could spiral into a rapid regulatory issue. Tesla is gently dipping its toes into full autonomy, and once they’re sure that Unsupervised FSD is far safer than an average human driver they can expand it to Tesla owners.
Tesla will also be rolling out Unsupervised FSD in California - and other regions of the US as they gain regulatory approval. Tesla’s FSD is a generalized solution - it doesn't need high-precision or HD mapping and local preparation before being rolled out - instead, Tesla’s biggest hold-backs are safety and improving their software.
As Tesla approaches the launch of the Robotaxi network, it makes us realize how many steps there really are to the puzzle. Tesla will need to have procedures in place on how to deal with issues such as a vehicle getting stuck, someone hitting an emergency button, or even an accident. Tesla will also need to launch its vehicle hubs that will be responsive for cleaning and charging the vehicles.
People go to manual driving to check their phone so that they don’t strike out/get beeped at - and then go back to FSD.
While June 2025 may seem rather aggressive to launch the autonomous service, it’s typical for Tesla to be overly optimistic and aggressive with deadlines, but it gives us a better indication of when they plan to launch Unsupervised FSD. Even if they miss the June launch, we’ll hopefully see the network begin this year, which will be a massive boost for Tesla and its shareholders.
When Can I Join the Robotaxi Fleet?
Tesla will be allowing owners to enroll their own vehicles in cities that are allowing Robotaxi - so if you live in Austin or other cities that have an approved Tesla Robotaxi network, you could get paid to add your vehicle to the Robotaxi fleet.
During the earnings call, Tesla announced that owners could add their vehicles to the Robotaxi fleet in 2026, although they weren’t more specific than that. This will be at least six months after the Robotaxi network launches.
Elon mentioned during the earnings call that Tesla needs to be supremely confident that the probability of injury or accident is extremely low before they allow FSD Unsupervised on customer vehicles. That’s rather interesting - because he didn’t mention liability - a question that often comes up for autonomous vehicles.
One of the points mentioned by both Ashok Elluswamy, Tesla’s VP of AI, as well as Elon was that if there is even a single minor incident - it’ll be headline news globally, even though an average of 40,000 drivers die a year in regular traffic accidents - the majority of which don’t even make local news.
We’ll have to wait and see in 2026 for what really happens for liability and insurance - because true autonomy will hinge on who is liable for what happens in an accident - the vehicle/software manufacturer or the owner of the vehicle.
FSD Unsupervised for Owners
FSD(U) - as we’re calling it - won’t be available for users initially while Tesla tests it with its fleets. Once Tesla gets enough testing done to ensure safety is at the level that it needs - they’ll begin rolling out FSD(U) to owners. Since Tesla expects to let owners add their vehicles to the Robotaxi fleet in 2026, we expect FSD(U) for vehicle owners to arrive sometime after this date.
Tesla will have more control of a vehicle while it’s being managed by its fleet, so it makes sense for FSD(U) for Tesla owners to arrive later in 2026 or even 2027.
Tesla is aiming for a safety level that is significantly higher than the average human driver - one magnitude higher. Right now, according to the Q4 Vehicle Safety Report, the average driver has an incident on average every 700,000 miles, while a Tesla has one on average every 1.08 million miles. On FSD or Autopilot, that number goes up significantly - to 5.94 million miles. Tesla is aiming to bring that number closer to 7 million miles before they significantly expand FSD(U) - the one-order of magnitude mark.
And it sounds like Elon will be happy to enable it - because he said the following at the earnings call: “People go to manual driving to check their phone so that they don’t strike out/get beeped at - and then go back to FSD.”
And it’s pretty true - it would be much safer if people didn’t do that. Now, getting FSD(U) on our vehicles is just a matter of time. So let’s watch Tesla cut red tape in 2025!
Launch Phases
Tesla will need to beat regulatory hurdles that will eventually challenge their rapid deployment. Tesla hopes to be able to deploy FSD Unsupervised with its Robotaxi fleets throughout the United States by the end of 2025, with it coming to Canada in 2026.
Tesla will be starting with Austin, Texas, where they’ve already obtained regulatory approval, and then move to other cities within the United States in the following months.
Currently, Tesla’s primary use of Unsupervised FSD is happening at Fremont, with vehicles driving themselves from the production line to the delivery lot and in downtown LA, where they’ve been testing with safety drivers to get employees around town. And at the factory - it's happening daily, and reliability - with thousands of vehicles moving from the line to the lot every day.
We imagine Tesla will launch FSD(U) in several phases, potentially looking something like this:
Test FSD(U) internally (being done now)
Launch the Robotaxi network in small areas for refinement
Expand and improve the network
Allow non-Tesla-owned vehicles (owners allowed to join)
Offer Unsupervised FSD to Tesla owners where Tesla will have less control over the vehicle
As many of you are, we’re really excited to see Tesla’s Robotaxis in the wild for the first time. Like everything else Tesla, expects the release of FSD(U) to be small and gradually grow. It may consist of only employees in Austin at first, or it may include a safety driver, or even be limited to a very small region. While some may be disappointed at first, remember how Tesla rolls out features. Iterations and improvements will come consistently and fast.
Tesla has been struggling to provide FSD updates for vehicles with Hardware 3 (HW3). What was once thought to be enough compute power to solve autonomy, is no longer able to handle the latest FSD updates.
Yesterday, Tesla finally confirmed that vehicles with HW3 will need to be upgraded to achieve Unsupervised FSD.
HW3 Upgrade Finally Confirmed
Musk had previously suggested that an upgrade might be necessary and Tesla would upgrade these vehicles if needed. However, during yesterday’s earnings call, Musk admitted that HW3 vehicles will, in fact, need to be upgraded. Tesla said that these upgrades will be performed free of charge for owners who have purchased the FSD package, leaving subscribers wondering what will happen to their cars.
Musk stated, “That's going to be painful and difficult, but we'll get it done. Now I'm kinda glad that not that many people bought the FSD package haha.” This appears to confirm that Tesla doesn’t plan on upgrading HW3 on vehicles that subscribe to FSD.
What About Subscription-Based FSD Owners?
While there are a lot of questions, one of the bigger ones is what happens to owners who have subscribed to FSD. Tesla didn’t touch on the topic, but if they’re not planning to upgrade HW3 subscribers, then they could potentially offer a paid retrofit. When the Model 3 was first released, it came standard with HW 2.5. At the time, Tesla said that you won’t need anything better unless you plan to buy FSD. Tesla ended up upgrading owners who had bought FSD for free, but non-FSD owners were required to pay for an upgrade.
Based on previous hardware upgrades—such as the HW2.5 to HW3 transition—a paid upgrade could cost between $1,000 to $3,000. However, it’s not clear what the upgrade to HW3 vehicles will be or how much it will cost even if a paid upgrade becomes available.
FSD on HW3
Musk also hinted that FSD was not selling as well as Tesla had hoped, which likely influenced the introduction of subscription-based FSD.
Meanwhile, Tesla continues to improve HW3-based FSD. FSD V12.6 offers major improvements in smoothness and is considered a “baby V13” with notable improvements over V12.5.4.2. Reverse capabilities are also expected to arrive in a future release for HW3 vehicles, so Tesla hasn’t stopped development just yet. However, Musk was clear that HW3 will continue to lag behind HW4 releases moving forward.
FSD V14 and the Future of HW3
Tesla has stated that FSD V14 will be another significant step toward achieving Unsupervised FSD. The increasing complexity of FSD models and their growing context sizes mean that HW3 is already not able to run the larger FSD V13 models, but according to Tesla, V14 will increase the AI model even further, making it nearly impossible to run on HW3. As AI models become increasingly larger and AI5’s impending arrival approaches, one wonders how long before HW4 can’t run the latest models.
However, Tesla appears confident that HW4 will be sufficient, given its plans to launch FSD-powered robotaxis later this year.
What Will the HW3 Upgrade Look Like?
While Tesla has confirmed the HW3 upgrade, specific details remain unknown. We know that it won’t just be an upgrade to hardware 4 since that computer consumes more power than HW3’s electrical harness can provide, and it also has a different form factor, making retrofitting difficult.
Instead, Tesla will likely have to develop a new FSD hardware unit tailored for the retrofit or modify existing components to fit HW3-equipped vehicles. The hardware will need to be at least as computationally capable as HW4, but use the power of a HW3 unit.
Tesla has also said that it has no plans to replace cameras during the upgrade, despite HW3 cameras having significantly lower resolutions than HW4’s. While Tesla appears confident that this won’t be an issue, owners have reasons to be concerned as Tesla recently increased video processing resolution on HW4 cameras to improve FSD performance.
Tesla’s confirmation of an HW3 upgrade certainly makes more owners comfortable. However, the lack of details leaves subscribers and others wondering what will happen to their vehicles. It also doesn’t do much to ease the frustration of dealing with slower and less capable FSD releases, especially when they pay the same amount as HW4 owners, who receive more features and a smoother ride.
While free upgrades will be available for those who bought FSD outright, subscription-based owners are left in limbo, with no details on potential paid upgrade options.
With FSD V14 on the horizon and HW3 vehicles already struggling with the latest models, this upgrade will be crucial to keep existing owners happy.
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