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.
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As December approaches, Tesla’s highly anticipated Holiday update draws closer. Each year, this eagerly awaited software release transforms Tesla vehicles with new features and festive flair. If you’re not familiar with Tesla’s holiday updates, take a look at what Tesla has launched in the Holiday update the past few years.
For this chapter in our series, we’re dreaming up ways Tesla could improve the charging experience and even add some additional safety features. So let’s take a look.
Destination State of Charge
Today, navigating to a destination is pretty straightforward on your Tesla. Your vehicle will automatically let you know when and where to charge, as well as for how long. However, you’ll likely arrive at your destination at a low state of charge.
Being able to set your destination state of charge would be an absolute game-changer for ease of road-tripping. After all, the best EV to road trip in is a Tesla due to the Supercharger network. It looks like Tesla may be listening. Last week, Tesla updated their app and hinted at such a feature coming to the Tesla app. A Christmas present, maybe?
Battery Precondition Options
While Tesla automatically preconditions your battery when needed for fast charging, there are various situations where manually preconditioning the battery would be beneficial.
Currently, there is no way to precondition for third-party chargers unless you “navigate” to a nearby Supercharger. If you need to navigate to a Supercharger that’s close by, the short distance between your location and the Supercharger will also not allow enough time to warm up the battery, causing slower charging times.
While we already mentioned Live Activities in the Tesla app wishlist, they’d be especially useful while Supercharging. Live Activities are useful for short-term information you want to monitor, especially if it changes often — which makes them perfect for Supercharging, especially if you want to avoid idle fees.
Vehicle-to-Load / Vehicle-to-Home Functionality
The Cybertruck introduced Tesla Power Share, Tesla’s name for Vehicle-to-Home functionality (V2H). V2H allows an EV to supply power directly to a home. By leveraging the vehicle’s battery, V2H can provide backup power during outages and reduce energy costs by using stored energy during peak rates.
Tesla Power Share integrates seamlessly with Tesla Energy products and the Tesla app. We’d love to see this functionality across the entire Tesla lineup. Recently a third party demonstrated that bidirectional charging does work on current Tesla vehicles – namely on a 2022 Model Y.
Adaptive Headlights for North America
While Europe and China have had access to the Adaptive Headlights since earlier this year, North America is still waiting. The good news is that Lars Moravy, VP of Vehicle Engineering, said that these are on their way soon.
Blind Spot Indication with Ambient Lighting
Both the 2024 Highland Model 3 Refresh and the Cybertruck already have ambient lighting features, but they don’t currently offer a practical purpose besides some eye candy. So why not integrate that ambient lighting into the Blindspot Warning system so that the left or right side of the vehicle lights up when there’s a vehicle in your blind spot? Currently, only a simple red dot lights up in the front speaker grill, and the on-screen camera will also appear with a red border when signaling.
Having the ambient lighting change colors when a vehicle is in your blind spot would be a cool use of the technology, especially since the Model Y Juniper Refresh and Models S and X are supposed to get ambient lighting as well.
Tesla’s Holiday update is expected to arrive with update 2024.44.25 in just a few short weeks. We’ll have extensive coverage of its features when it finally arrives, but in the meantime, be sure to check out our other wishlist articles:
It’s time for another dive into how Tesla intends to implement FSD. Once again, a shout out to SETI Park over on X for their excellent coverage of Tesla’s patents.
This time, it's about how Tesla is building a “universal translator” for AI, allowing its FSD or other neural networks to adapt seamlessly to different hardware platforms.
That translating layer can allow a complex neural net—like FSD—to run on pretty much any platform that meets its minimum requirements. This will drastically help reduce training time, adapt to platform-specific constraints, decide faster, and learn faster.
We’ll break down the key points of the patents and make them as understandable as possible. This new patent is likely how Tesla will implement FSD on non-Tesla vehicles, Optimus, and other devices.
Decision Making
Imagine a neural network as a decision-making machine. But building one also requires making a series of decisions about its structure and data processing methods. Think of it like choosing the right ingredients and cooking techniques for a complex recipe. These choices, called "decision points," play a crucial role in how well the neural network performs on a given hardware platform.
To make these decisions automatically, Tesla has developed a system that acts like a "run-while-training" neural net. This ingenious system analyzes the hardware's capabilities and adapts the neural network on the fly, ensuring optimal performance regardless of the platform.
Constraints
Every hardware platform has its limitations – processing power, memory capacity, supported instructions, and so on. These limitations act as "constraints" that dictate how the neural network can be configured. Think of it like trying to bake a cake in a kitchen with a small oven and limited counter space. You need to adjust your recipe and techniques to fit the constraints of your kitchen or tools.
Tesla's system automatically identifies these constraints, ensuring the neural network can operate within the boundaries of the hardware. This means FSD could potentially be transferred from one vehicle to another and adapt quickly to the new environment.
Let’s break down some of the key decision points and constraints involved:
Data Layout: Neural networks process vast amounts of data. How this data is organized in memory (the "data layout") significantly impacts performance. Different hardware platforms may favor different layouts. For example, some might be more efficient with data organized in the NCHW format (batch, channels, height, width), while others might prefer NHWC (batch, height, width, channels). Tesla's system automatically selects the optimal layout for the target hardware.
Algorithm Selection: Many algorithms can be used for operations within a neural network, such as convolution, which is essential for image processing. Some algorithms, like the Winograd convolution, are faster but may require specific hardware support. Others, like Fast Fourier Transform (FFT) convolution, are more versatile but might be slower. Tesla's system intelligently chooses the best algorithm based on the hardware's capabilities.
Hardware Acceleration: Modern hardware often includes specialized processors designed to accelerate neural network operations. These include Graphics Processing Units (GPUs) and Tensor Processing Units (TPUs). Tesla's system identifies and utilizes these accelerators, maximizing performance on the given platform.
Satisfiability
To find the best configuration for a given platform, Tesla employs a "satisfiability solver." This powerful tool, specifically a Satisfiability Modulo Theories (SMT) solver, acts like a sophisticated puzzle-solving engine. It takes the neural network's requirements and the hardware's limitations, expressed as logical formulas, and searches for a solution that satisfies all constraints. Try thinking of it as putting the puzzle pieces together after the borders (constraints) have been established.
Here's how it works, step-by-step:
Define the Problem: The system translates the neural network's needs and the hardware's constraints into a set of logical statements. For example, "the data layout must be NHWC" or "the convolution algorithm must be supported by the GPU."
Search for Solutions: The SMT solver explores the vast space of possible configurations, using logical deduction to eliminate invalid options. It systematically tries different combinations of settings, like adjusting the data layout, selecting algorithms, and enabling hardware acceleration.
Find Valid Configurations: The solver identifies configurations that satisfy all the constraints. These are potential solutions to the "puzzle" of running the neural network efficiently on the given hardware.
Optimization
Finding a working configuration is one thing, but finding the best configuration is the real challenge. This involves optimizing for various performance metrics, such as:
Inference Speed: How quickly the network processes data and makes decisions. This is crucial for real-time applications like FSD.
Power Consumption: The amount of energy used by the network. Optimizing power consumption is essential for extending battery life in electric vehicles and robots.
Memory Usage: The amount of memory required to store the network and its data. Minimizing memory usage is especially important for resource-constrained devices.
Accuracy: Ensuring the network maintains or improves its accuracy on the new platform is paramount for safety and reliability.
Tesla's system evaluates candidate configurations based on these metrics, selecting the one that delivers the best overall performance.
Translation Layer vs Satisfiability Solver
It's important to distinguish between the "translation layer" and the satisfiability solver. The translation layer is the overarching system that manages the entire adaptation process. It includes components that analyze the hardware, define the constraints, and invoke the SMT solver. The solver is a specific tool used by the translation layer to find valid configurations. Think of the translation layer as the conductor of an orchestra and the SMT solver as one of the instruments playing a crucial role in the symphony of AI adaptation.
Simple Terms
Imagine you have a complex recipe (the neural network) and want to cook it in different kitchens (hardware platforms). Some kitchens have a gas stove, others electric; some have a large oven, others a small one. Tesla's system acts like a master chef, adjusting the recipe and techniques to work best in each kitchen, ensuring a delicious meal (efficient AI) no matter the cooking environment.
What Does This Mean?
Now, let’s wrap this all up and put it into context—what does it mean for Tesla? There’s quite a lot, in fact. It means that Tesla is building a translation layer that will be able to adapt FSD for any platform, as long as it meets the minimum constraints.
That means Tesla will be able to rapidly accelerate the deployment of FSD on new platforms while also finding the ideal configurations to maximize both decision-making speed and power efficiency across that range of platforms.
Putting it all together, Tesla is preparing to license FSD, Which is an exciting future. And not just on vehicles - remember that Tesla’s humanoid robot - Optimus - also runs on FSD. FSD itself may be an extremely adaptable vision-based AI.
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