Apple has released its latest software update for iPhone, iPad, and MacOS, along with other systems. While the update includes many new features, such as RCS text message support, a customizable Control Center and many other features, we’ll focus on the ones that apply to Tesla and the Tesla app.
Control Center
With iOS and iPadOS 18, Apple overhauled Control Center. Visually, it remains very similar to its previous incarnation, except that you can now customize it in several ways. First, you can resize each button. Most icons can be customized so that they take up a single square, two spots or four. While Tesla doesn’t support any native actions for Control Center yet, you can create your own shortcut using Apple’s Shortcuts app and add it to Control Center (see below). The action can preheat/precool the cabin, start charging, unlock the vehicle or many others. To set a custom action, simply swipe down to Control Center, tap the plus (+) icon on the top-left corner, and choose Add a Control at the bottom.
Not a Tesla App
Customize Tesla App Icon
iOS 18 also adds support for dark icons and customizable tint options. That means that you now have a degree of control over what the Tesla app icon looks like. To use dark icons while Dark Mode is active on the phone, tap and hold on any app icon and choose Edit Home Screen. When the icons start jiggling, tap the Edit button on the top left and choose Customize.
At the bottom of the screen, you’ll now be able to choose between various methods of customizing your app icons. You can pick from two app icon sizes, choose light/dark app icons and choose a color for tinting all icons.
The Tesla dark icon is a red T on a black background, while the light icon remains the same white T on a red background. The Tinted option allows you to tint all of your app icons in your preferred shade.
Lock Screen Buttons
Not a Tesla App
The iPhone has had two lock screen icons for several years, which include shortcuts to the flashlight and camera apps. However, with this update, you can now swap out those icons for other apps or custom actions. Since the Tesla app doesn’t support any actions yet, you’ll need to create a shortcut first, then you can apply it here or to the Control Center. Creating a shortcut for cabin preconditioning is one of the most useful options, as it gives you one-touch access to cooling your vehicle.
To set up custom lock screen buttons you’ll want to lock your phone first. then tap on your wallpaper in any blank area. Choose customize and then choose the lock screen. You’ll then see several options to add widgets or remove the icons from your lock screen. Start by removing one of the icons at the bottom, then tap the + button to add a new one. This could be the Tesla app, or a specific shortcut. If you want to use a shortcut, you’ll want to choose Shortcut Control Title. Once the menu comes up, you simply pick the shortcut you created.
Locking Tesla to Face ID
With iOS 18, Apple also introduced the ability to lock or hide certain apps. You can lock an app so that it requires Face ID before someone is able to access it. To set it up, just tap and hold on the app icon you’d like to lock and then choose the “Require Face ID” option. Like most things on iOS, if Face ID fails, you can still open the app with your phone’s passcode. If you prefer to hide an app, the process is similar. You’ll want to choose Require Face ID, and then the phone will prompt you whether you want to just require Face ID or if you’d like to hide the app.
If you choose to hide the app, the app icon will be removed from your home screen, and the app will only show up in the Hidden folder in the App Library. To access the App Library, swipe left after you get to the last home screen. To bring up a list of your hidden apps, tap the Hidden folder at the bottom and authenticate with Face ID.
Keep in mind that locking or hiding your app comes with several disadvantages. If you lock your app, then all Tesla notifications won’t be readable without first authenticating with Face ID.
Creating an Apple Shortcut & Using Siri
Not a Tesla App
You can create your own custom action with Apple Shortcuts. They can be extremely simple, like unlocking your vehicle, and require only a couple of minutes to set up.
To create a shortcut that could be utilized in Control Center, on the Lock Screen or as the Action button, open the Apple Shortcuts app.
Once you’re there, tap on the plus (+) sign at the top right corner of the app. On the bottom half of the screen, scroll up until you find the Tesla app and tap it. You’ll then see a list of all supported Tesla functions.
You can tap on any action such as Start under ‘Precondition Vehicle’ or Unlock vehicle. After choosing your preferred option, you’ll need to choose the vehicle it applies to, even if you have a single vehicle on your account. Simply tap the Choose Vehicle text and pick your car.
If you’d like to name the action, you can tap on the name with the down arrow at the top center of the screen and choose rename. After renaming your action, you can simply tap done and exit the app.
You can now run the action by simply saying its name when you bring up Siri, such as “Hey Siri, start car.” You can also take this shortcut and add it to Control Center or the lock screen for quick access.
Action Button
Not a Tesla App
With the new iPhone 16 model, Apple has replaced the mute/vibrate toggle with the Action button for all phone models. The Action button can be used for any action you’d like, but assigning it to a shortcut allows you to perform certain Tesla functions like the ones we mentioned earlier that could be added to Control Center or the lock screen.
Cooling down the cabin can now be a single button push away, and you can even push it without removing your phone from your pocket.
Until Tesla adds native support for actions that could be added to different parts of iOS 18, creating a simple shortcut is your best bet to take advantage of the latest iOS 18 features.
Tesla launched two FSD updates simultaneously on Saturday night, and what’s most interesting is that they arrived on the same software version. We’ll dig into that a little later, but for now, there’s good news for everyone. For Hardware 3 owners, FSD V12.6.1 is launching to all vehicles, including the Model 3 and Model Y. For AI4 owners, FSD V13.2.4 is launching, starting with the Cybertruck.
FSD V13.2.4
A new V13 build is now rolling out to the Cybertruck and is expected to arrive for the rest of the AI4 fleet soon. However, this build seems to be focused on bug fixes. There are no changes to the release notes for the Cybertruck with this release, and it’s unlikely to feature any changes when it arrives on other vehicles.
FSD V12.6.1 builds upon V12.6, which is the latest FSD version for HW3 vehicles. While FSD V12.6 was only released for the redesigned Model S and Model X with HW3, FSD V12.6.1 is adding support for the Model 3 and Model Y.
While this is only a bug-fix release for users coming from FSD V12.6, it includes massive improvements for anyone coming from an older FSD version. Two of the biggest changes are the new end-to-end highway stack that now utilizes FSD V12 for highway driving and a redesigned controller that allows FSD to drive “V13” smooth.
It also adds speed profiles, earlier lane changes, and more. You can read our in-depth look at all the changes in FSD V12.6.
Same Update, Multiple FSD Builds
What’s interesting about this software version is that it “includes" two FSD updates, V12.6.1 for HW3 and V13.2.4 for HW4 vehicles. While this is interesting, it’s less special when you understand what’s happening under the hood.
The vehicle’s firmware and Autopilot firmware are actually completely separate. While a vehicle downloading a firmware update may look like a singular process, it’s actually performing several functions during this period. First, it downloads the vehicle’s firmware. Upon unpacking the update, it’s instructed which Autopilot/FSD firmware should be downloaded.
While the FSD firmware is separate, the vehicle can’t download any FSD update. The FSD version is hard-coded in the vehicle’s firmware that was just downloaded. This helps Tesla keep the infotainment and Autopilot firmware tightly coupled, leading to fewer issues.
What we’re seeing here is that HW3 vehicles are being told to download one FSD version, while HW4 vehicles are being told to download a different version.
While this is the first time Tesla has had two FSD versions tied to the same vehicle software version, the process hasn’t actually changed, and what we’re seeing won’t lead to faster FSD updates or the ability to download FSD separately. What we’re seeing is the direct result of the divergence of HW3 and HW4.
While HW3/4 remained basically on the same FSD version until recently, it is now necessary to deploy different versions for the two platforms. We expect this to be the norm going forward, where HW3 will be on a much different version of FSD than HW4. While each update may not include two different FSD versions going forward, we may see it occasionally, depending on which features Autopilot is dependent on.
Thanks to Greentheonly for helping us understand what happened with this release and for the insight into Tesla’s processes.
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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