How Tesla’s “Universal Translator” Will Streamline FSD for Any Platform

November 20, 2024

By Karan Singh

Not a Tesla App

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.

Is Tesla Planning to Add Steam Support to All Vehicles?

December 11, 2024

By Karan Singh

Not a Tesla App

Yesterday, we reported that Tesla updated their Steam integration on Model S and Model X vehicles. The update was part of their 2024 Holiday Update, but it looks like there may be more to this than a simple update.

Steam, a video game library app, makes it easy for users to buy or launch games on their computers. However, a couple of years ago, Valve, who created Steam, launched their own standalone device, the Steam Deck. The Steam Deck runs a custom OS based on Linux.

Steam Launch

When Tesla launched the redesigned Model S and Model X, Tesla introduced a dedicated gaming GPU with 16GB of RAM and touted the ability to play top-tier PC games in Tesla vehicles.

In 2022, Tesla finally launched the Steam app for the Model S and Model X as part of its 2022 Holiday Update. The Steam app runs Steam OS, the same OS as the Steam Deck in a virtual environment.

However, earlier this year, Tesla stopped including the GPU and Steam (Beta) in their vehicles, and we haven’t seen any updates to the Steam in quite some time. In fact, we thought Tesla was axing their gaming-on-the-go dreams.

SteamOS Update

The Steam app, which is still in Beta, is getting an interesting update for the Model S and Model X vehicles with the discrete GPU.

Those vehicles received an update to SteamOS 3.6 - the same version of SteamOS that runs on the Steam Deck. While nothing has visually changed, there’s a long list of performance optimizations under the hood to get things running smoother.

Comparing Steam Deck to Tesla Vehicles

Let’s take a look at the Steam Deck - according to Valve, its onboard Zen4 CPU and GPU combined push a total of 2 TFlops of data, which is fairly respectable, but much lower than today’s home consoles. The Steam Deck is capable of 720p gaming fairly seamlessly on low-to-medium settings on the go and is also built on the AMD platform.

AMD-equipped Teslas, including the Model 3 and Model Y, are packing an older Zen+ (Zen 1.5) APU (processor with a combined CPU and GPU). AMD claims that the V1000 - the same embedded chip as on AMD Tesla vehicles (YE1807C3T4MFB), brings up to 3.6 TFLops of processing power with it, including 4K encoding and decoding with the integrated GPU on board.

While that’s not enough for 4K gaming or comparable to a full-blown console or desktop GPU, that’s enough raw horsepower for light gaming and is currently more powerful than the Steam Deck.

The Model S and Model X’s GPU brings that up to about 10TFlops of power - comparable to modern consoles like the Xbox Series X at 12 TFlops.

Steam Gaming for All Vehicles?

The fact that Tesla is updating SteamOS even though the feature is no longer available in any new vehicles could indicate that Tesla is not only bringing Steam back to Teslas but that it’s going to play a much bigger role.

While SteamOS is run in a virtual environment on top of Tesla’s own OS, we could see Tesla bring SteamOS to all of its current vehicles, including the Model 3, Model Y, and Cybertruck. Steam in these vehicles would likely support any game that’s capable of running on the Steam Deck.

We think this Steam update, which includes performance improvements and a variety of fixes, has quietly passed under most people’s radars. This could be a very exciting update for those who enjoy gaming, especially for those who love to do it in their Tesla.

Tesla Holiday Update Weather Features: All the Small Details

December 11, 2024

By Karan Singh

Robert Rosenfeld / YouTube

As part of Tesla’s 2024 Holiday Update, Tesla included two awesome new features - Weather at Destination and the long-awaited Weather Radar Overlay. These two features are big upgrades built upon the weather feature that was added in update 2024.26. The original weather feature added an hourly forecast, as well as the chance of precipitation, UV index, Air Quality Index, and other data.

However, this update also added some smaller weather touches, such as the vehicle alerting you if the weather at the destination will be drastically different from the current weather.

Not a Tesla App

Weather At Destination

When you’re navigating to a destination and viewing the full navigation direction list, the text under the arrival time will show you the expected weather next to your destination. You can also tap this, and the full weather pop-up will show up, showing your destination's full set of weather information.

Note the weather under the arrival time

Not a Tesla App

You can also tap the weather icon at the top of the interface at any time and tap Destination to switch between the weather at your current location and the weather at your destination.

You’re probably considering that the weather at your destination doesn’t matter when you’re three hours away - but that’s all taken into account by the trip planner. It will add in both charge time and travel time and show you the weather at your destination at your expected arrival time.

And if the weather is drastically different or inclement, such as rain or snow, while you’ve got sunshine and rainbows - the weather will be shown above the destination ETA for a few moments before it tucks itself away.

Tesla also recently introduced a new voice command. Asking, “What’s the weather?” or something similar will now bring up Tesla’s weather popup.

The weather pop-up above the ETA

Not a Tesla App

One limitation, though—if you’re planning a long road trip that is more than a day of driving, the weather at destination feature won’t be available until you get closer.

Weather Radar Overlay

As part of the improvements to weather, Tesla has also added a radar overlay for precipitation. You can access the new radar overlay by tapping the map and then tapping the weather icon on the right side of the map. It’ll bring up a radar overlay centered on your vehicle. It’ll animate through the radar data over the last 3 hours so that you can see the direction of the storm, but you can also pause it at any point.

You’re able to scroll around in this view and see the weather anywhere, even if you zoom out. It also works while you’re driving, although it can be a little confusing if you’re trying to pay attention to the navigation system. If you like to have Points of Interest enabled on your map, the weather overlay will hide POIs except for Charging POIs.

Requirements / Data

Unfortunately, you’ll need Premium Connectivity for any of the weather features to work, and being on WiFi or using a hotspot will not be enough to get the data to show up. The data, including the weather radar, is provided by The Weather Channel.

As for supported models, weather and weather at destination are available on all vehicles except for the 2012-2020 Model S and Model X. The weather radar has more strict requirements and requires the newer AMD Ryzen-powered infotainment center available on the 2021+ Model S and Model X and more recent Model 3 and Model Y vehicles.