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Tesla’s Neural Network adaptability to hardware highlighted in new patent application

(Credit: Tesla Driver/YouTube)

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Tesla’s developments in the artificial intelligence arena are one of the most important aspects of its current and future technology, and this includes adapting neural networks to various hardware platforms. A recent patent publication titled “System and Method for Adapting a Neural Network Model On a Hardware Platform” provides a bit of insight into how the electric car maker is taking on the challenge.

In general, a neural network is a set of algorithms designed to gather data and recognize patterns from it. The particular data being collected depends on the platform involved and what kind of information it can send to the network, i.e., cameras/image data, etc. Differences between platforms mean differences in the neural network algorithms, and adapting them is something time consuming for developers. Just as apps have to be programmed to work based on the operating system or hardware on a phone or tablet, for example, so too do neural networks. Tesla’s answer to the adaptation issue is automation (of course).

During the adaptation process of a neural network to specific hardware, decisions must be made by a software developer based on available options built into the hardware being used. Each of these options, in turn, usually requires research, hardware documentation review, and impact analysis, with each set of options chosen, eventually adding up to a configuration for the neural network to use. Tesla’s application calls these options “decision points,” and they are a vital part of how their invention functions.

Credit: Tesla/USPTO

According to the application, after plugging in a neural network model and the specific hardware platform information for adaptation, software code traverses the network to learn where the decision points are, then runs the hardware parameters against those points to provide available configurations. More specifically, the software method looks at the hardware constraints (such as processing resources and performance metrics) and generates setups for the neural network that will satisfy the requirements for it to operate correctly. From the application:

In order to produce a concrete implementation of an abstract neural network, a number of implementation decisions about one or more of system’s data layout, numerical precision, algorithm selection, data padding, accelerator use, stride, and more may be made. These decisions may be made on a per-layer or per-tensor basis, so there can potentially be hundreds of decisions, or more, to make for a particular network. Embodiments of the invention take many factors into account before implementing the neural network because many configurations are not supported by underlying software or hardware platforms, and such configurations will result in an inoperable implementation.

Credit: Tesla/USPTO

Tesla’s invention also provides the ability to display the neural network configuration information on a graphical interface to make assessment and selection a bit more user friendly. For instance, different configurations could have different evaluation times, power consumption, or memory consumption. Perhaps an analogy for this process would be selecting configurations based on differences between Track Mode and Range Mode but instead for how you’d want your AI to work with your hardware.

This patent application looks to be one of the products of Tesla’s reported acquisition of DeepScale, an AI startup focused on Full Self Driving and designing neural networks for small devices. The listed inventor, Dr. Michael Driscoll, was a Senior Staff Engineer for DeepScale before transitioning to a Senior Software Engineer position at Tesla. Prior CEO of DeepScale, Dr. Forrest Iandola, also transitioned to Tesla as a Senior Staff Machine Learning Scientist before moving on to independent research this year.

Accidental computer geek, fascinated by most history and the multiplanetary future on its way. Quite keen on the democratization of space. | It's pronounced day-sha, but I answer to almost any variation thereof.

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Tesla Summer Update begins rolling out: a look at the new features

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Credit: Tesla

Tesla has started to deploy the 2026 Summer Update to owners across its fleet, and among the biggest changes are improvements to Navigation, a new startup animation for the Model 3 and Model Y, Caraoke scoring, and new capabilities for Grok.

As the update has started making its way to some cars, we can now see a few of the features operating in real-time. We will show you what some of the new features look like in this article, along with some additional details on what changed.

Not all of the new features in the 2026 Summer Update have quite made an appearance, but some of them have, so we’ll show those here:

New Animation Screen for 3/Y

Tesla is rolling out a new startup animation for Tesla Model 3 and Model Y owners. This is present in Launch Edition and Performance Model 3 and Model Y, but other trim levels do not have anything like this.

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Owners can adjust the color associated with the startup animation to suit their preferences. It is a surprise that more automakers do not focus on this animation for their vehicles; it can be a great first impression piece and make the car immediately feel more luxurious.

Tesla has included this on more premium trims, but it is nice to see it on the Model 3 and Model Y.

Grok Improvements

Grok can now adjust more things in the car outside of the Navigation system. Now, drivers can adjust anything from climate to driving settings by simply speaking to the AI assistant in the car:

You don’t even have to push a button, either. Instead, you can just say “Hey, Grok,” if you have it enabled. That feature rolled out with the 2026 Spring Update just a few months back.

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This is a great feature, especially pertinent for the Robotaxi platform, as there will be no buttons inside the Cybercab when it eventually starts giving rides to the public. It also broadens Grok’s capabilities, which were relatively limited in terms of vehicle setting adjustments beforehand.

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Tesla briefly offered this Robotaxi part for your personal car

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Credit: @tpgoebel | X

Tesla briefly offered one Robotaxi part in its Parts Catalog for your personal car, only to remove it just a short time after it was first noticed.

Tesla’s Robotaxi camera washer apparatus was briefly available for purchase on the company’s Online Parts Catalog. The camera washer was first noticed on Model Y Robotaxi vehicles about six months ago in Austin.

First noticed by Not a Tesla App, the Camera Washer entries appeared for the new “Juniper” Model Y under a category called “Halo,” which has also now disappeared. Interestingly, Halo probably is related to Tesla’s internal “Project Halo,” which was a project that aimed to retrofit customer-owned Model Ys into functional Robotaxis.

This hardware addition would likely be required for the vehicle to operate as a Robotaxi, as the Camera Washer seems to be a non-negotiable part of the vision-based system Tesla utilizes for self-driving efforts.

However, this part has since been removed and is no longer visible on the EPC.

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Now the true question lingers: Why would Tesla add this Camera Washer to the Model Y parts catalog? Is it planning to make it available for owners to utilize on their own cars for personal use, or will it become a prerequisite for Robotaxi operation in customer-owned cars?

While discussing the upgrade options for Hardware 3 vehicles during the Q1 Earnings Call, Tesla CEO Elon Musk had said that the company could establish small, satellite shops that would upgrade cameras and self-driving computers. Perhaps this same strategy could be utilized for vehicles that want to be included in Robotaxi but do not have the correct hardware.

AI4 is currently represented as capable of unsupervised self-driving, and the same was said about HW3 at one point, only for Tesla to admit last quarter that it would, unfortunately, not be possible. Perhaps AI4 vehicles might need this camera washer as a prerequisite, just as HW3 cars will need that camera and computer upgrade.

This could be the first hint of that’s where we are headed.

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Tesla Robotaxi gets sweeping but polarizing change

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Credit: Tesla

Tesla has started rolling out a broader change to the ride experience for its Robotaxi fleet by silencing turn signals, but the change is certainly polarizing.

Tesla has generally made it clear that its purpose-built ride-hailing platform, Robotaxi, will cater to the rider in nearly every way possible. This includes having climate preferences, music, and other personal settings loaded up in the car as the rider enters.

But Tesla is taking it a step further by muting turn signal chimes altogether, a change that appears to be a way to make the ride more peaceful:

However, there are a handful of people who are not thrilled about this change. Turn signals are a conditioned part of the human mind for those who ride in a car regularly.

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Taking a turn without one feels strange and odd, and not hearing it click while activated could set off some alarms for riders, who might use the noise as confirmation that other drivers know of their intention to turn.

Turn signal noises are still audible in customer cars, so if you use FSD in your personal vehicle, you will still hear the turn signal.

The move is certainly one that is unique, but not one that separates it from other ride-sharing services. In a normal car, the clicking sound confirms to the driver that the blinker is active. In a fully driverless Robotaxi, that feedback serves no purpose for passengers, other than peace of mind.

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