As a continuation of our series on Tesla’s patents, we’re taking a look at how Tesla optimizes the performance of AI - FSD, in this case - in autonomous vehicles and robots. Patent WO2024073115A1 goes over efficiently running complex AI models on specialized hardware.
Before we dive into this article, we recommend reading our article on How FSD Works and our other article on Tesla’s Universal Translator for streamlining FSD deployments. While they’re not necessary, the background knowledge will help you appreciate all the details behind how Tesla does their optimization.
Just like before, we’ll be breaking this down into sections and making them as easily understandable as possible.
AI Subnetworks
FSD isn’t a monolithic entity - it is composed of smaller, specialized sub-networks, each dedicated to a specific aspect or function of autonomous operation. This modular design means that Tesla can work on improving one or all sections through training. When one section is improved, the end-to-end nature of the AI also means that the other sections will learn to adapt to the improvements and, therefore, perform better. It also allows for more efficient processing and adaptability during deployment and initial platform training.
These sub-networks might be responsible for tasks such as:
Recognizing and interpreting traffic signals
Detecting and tracking moving objects including vehicles, pedestrians, cyclists, and more
Maintaining lane position and navigating roads
Generating 3D maps of the surrounding environment
Planning paths and making real-time driving decisions
This division of labor allows FSD to handle the complexities of autonomous driving with greater efficiency and precision
Tailored Compilers
Different hardware components are good at different things - and they also require different types of instructions. CPUs, GPUs, and specialized AI accelerators (NPUs) all have unique architecture and capabilities.
Tesla uses a compiler toolchain to translate FSD into machine code that is specifically tailored to each hardware component. This ensures that instructions are executed optimally on each processor, maximizing performance and efficiency.
Strategic Assignment
To further optimize performance, Tesla employs a system that intelligently assigns each FSD sub-network to the most suitable hardware component. This ensures that computationally demanding tasks are handled by the most powerful processors while simpler tasks are delegated to more efficient units.
This strategic assignment of tasks maximizes the overall efficiency of the system, ensuring that each component operates within its optimal performance range.
Optimized Scheduling
The order in which the hardware executes instructions also plays a crucial role in performance. Tesla's system includes an "execution scheduler" that determines the most efficient sequence of operations, minimizing delays and maximizing real-time responsiveness.
This optimized scheduling ensures that the FSD can react quickly and make informed decisions in dynamic driving situations - or quick-response situations with Optimus - like catching a ball.
While the demo here has been confirmed to be teleoperated, Tesla has said they’re working to let Optimus do this autonomously in the future.
To reduce the computational burden and power consumption of FSD, Tesla employs a technique called "quantization-aware training." This involves training FSD to work with lower-precision numbers, which require less processing power and memory. Essentially - rounding.
This approach allows the AI to operate efficiently without significantly compromising accuracy, striking a balance between performance and resource utilization.
Clock Synchronization
In hardware systems with multiple chips, maintaining precise timing is crucial for accurate and synchronized operation. Tesla's system incorporates mechanisms to synchronize the clocks of all processing units, preventing timing errors and ensuring seamless coordination between different components.
This precise clock synchronization is essential for FSD to make accurate real-time calculations and respond effectively to changing conditions.
Redundancy and Failover
To ensure reliability and safety, Tesla's system supports redundant hardware configurations. This means that if a critical component fails, a backup component can seamlessly take over, preventing disruptions in operation.
This redundancy and failover capability is crucial for maintaining the safety and integrity of autonomous systems, especially when driving. Tesla has built-in both physical and software redundancy to FSD, ensuring that it maintains a minimum standard of safety when operating autonomously.
In Simpler Terms…
Imagine a large company (FSD) with different departments (sub-networks) responsible for specific tasks. Each department has its own specialized tools and equipment (hardware components). Tesla's system acts like an efficient management structure, assigning the right tasks to the right departments, providing them with the appropriate tools, and coordinating their efforts for optimal productivity and performance.
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Tesla recently introduced Buy Now, Pay Later (BNPL) payment options in the United States and Canada for items in the Tesla Shop, letting owners pay later for new vehicle accessories.
However, with Tesla app update 4.46, they’re expanding support to a much more critical area — Tesla Service. Qualifying owners in the U.S. and Canada will now be able to use Pay Later options for service performed by Tesla, which includes maintenance or repairs.
Services are provided by Affirm and Klarna, as per Mark Fonte, a Senior Software Engineer working on the Tesla app.
The new feature is seamlessly integrated into the existing service workflow within the Tesla app.
On the Service Estimate, before work on the vehicle begins, you will see a new message on the estimate screen: Pay over time - see if you qualify.
Tapping this link opens the payment calculator, which allows you to view potential payment structures and monthly costs. This provides a clear picture of what a payment plan would look like before you commit to servicing your vehicle.
Additionally, after service is complete and you are ready to pay, the final payment screen will present Affirm and Klarna (region-dependent) as selectable payment methods, alongside the usual options of Tesla Credit or your primary payment card.
Tapping Affirm or Klarna here will reopen the payment calculator, and a confirmation prompt will appear before selecting either BNPL option.
Overall, the integration of BNPL providers for service is a thoughtful one for vehicle owners. The terms can vary widely, so it’s important to compare them to other payment options you may have access to. The additional financial flexibility, when faced with a large repair bill, allows more owners to get their vehicle professionally and properly serviced by Tesla.
For those getting larger work done, such as high-voltage battery pack replacements, this is an excellent option to spread payments over a longer period, helping reduce the burden of vehicle repair.
With the launch of Tesla’s Robotaxi Network, we didn't just get a peek into the future of transportation—we got a detailed look at the next version of FSD.
Videos from early access riders revealed some additional capabilities over current public FSD builds, showing off how it handles emergency vehicles and more.
Safety First for First Responders
One of the biggest changes in FSD’s capabilities is its improved handling of emergency vehicles. During a ride in Austin, Robotaxi is seen identifying an approaching ambulance using a combination of visual and audio data, activating its turn signal, and smoothly pulling over to the side of the road to let the ambulance by (video below).
This is a driving task that requires more than simple awareness of laws. It requires reasoning skills to determine where to move the vehicle to create a safe path, as well as the ability to quickly identify an ambulance or another emergency service vehicle with its sirens and lights activated. Understanding the context and executing a safe and predictable maneuver is crucial, as a wrong maneuver could actually make matters worse.
For FSD and Robotaxi to gain both public trust and regulatory approval, this skill is non-negotiable, and Tesla demonstrated its advancements right here. It’s not surprising Tesla added this ability before Robotaxis made it to public roads.
How does a fleet of Robotaxis keep its eyes clean without constant human intervention? Well, a clever new feature that Tesla has previously hinted at in their FSD release notes provides the answer. Robotaxi can now trigger a specific wiper and washer fluid sequence designed to clean the main front-facing cameras.
This might seem like a small detail, but it’s a brilliant solution to one of Tesla’s primary challenges - maintaining sensor clarity. While the vehicle could simply wipe the windshield multiple times, this is a clever solution to clean the most important area of the windshield as thoroughly as possible by focusing extra wiper fluid and wipes on that area.
Complex Maneuvers
Two areas where current builds of FSD V13.2.9 sometimes show hesitation are U-turns and navigating busy parking lots. The latest Robotaxi build appears to improve on both of these areas.
This first video shows a Robotaxi performing a flawless U-turn with no hesitation, and then smoothly switching lanes to take a turn.
Another video on X shows FSD’s updated confidence in navigating a complex parking lot for a precise drop-off. Today’s builds can sometimes struggle in parking lots, being slow and overly cautious when not needed, or too confident elsewhere. This appears to have been improved in these Robotaxi FSD builds with improved path planning and confidence.
Tesla Robotaxi service is just so smooth. Handles parking lots very well, noticeably better than the competitors pic.twitter.com/D5OxSrajCW
We’re also likely to see FSD begin to handle more complex destination options, including parking garages and driveways, which have been promised features for almost a year. The Robotaxi FSD build has also gained the ability to safely pull over on a road, similar to the ambulance example above, but it uses this capability to drop off and pick up passengers. This is a feature that was mentioned in FSD v13.2’s Upcoming Improvements section.
Better Nighttime Performance
Driving at night presents additional challenges, including headlight glare and reduced visibility. The latest version of FSD appears to handle it with almost the same grace as it does during the day. Remember that Tesla’s Robotaxis are available up until midnight. Early access riders mentioned that FSD is far smoother and is a step up from the behavior of current FSD builds.
Impressive nighttime performance from Tesla Robotaxi, dropping us off at In-N-Out as smoothly as it did during the day. pic.twitter.com/yQOhphtR0q
Now, what happens when a passenger feels unsafe or has a critical question? Tesla has placed two key buttons on the rear screen for just those purposes. Users are given control over the ability to Call Support, which almost instantly connects them with a real human agent at Tesla’s Robotaxi Operations Center via video call.
Here’s what happens when you hit the support button in Tesla’s Robotaxi’s.
While it isn’t a fundamental driving feature, it does mean that Tesla’s team can provide support to Robotaxi vehicles remotely, like issuing directive commands to have a vehicle proceed straight, rather than attempting to turn through a gated community.
The other option, Pull Over, allows a rider to immediately request the vehicle to safely pull over, which it will do when it can find a safe and open location. At this point, you can either continue your trip or get out of the Robotaxi.
Both options prompt you with an “Are You Sure?” button before letting you continue, which means you won’t have your Robotaxi ride come to an abrupt stop if you tap the ‘Pull Over’ button by accident.
What This Means for Tesla Owners
These features are likely to be included in future FSD builds. This is essentially the new benchmark by which to judge FSD, at least once it begins rolling out to customer vehicles.
Many of the core driving improvements, such as the more confident maneuvering and emergency vehicle response, will make their way to the wider fleet in upcoming FSD updates.
Remember - Robotaxi isn’t just a service, it is also a preview of Tesla’s driverless FSD builds.
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