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Tesla’s Neural Network adaptability to hardware highlighted in new patent application
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.
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.”
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.
Tesla has expanded the footprint of a massive safety feature worldwide with a recent Software Update labeled as 2026.20.6. The expansion of the “Blind Spot Warning While Parked” feature represents the more widespread availability of the feature, which aims to prevent “dooring.”
Dooring is when a driver or passenger opens a car door into the path of an oncoming road user, usually a cyclist or motorcyclist. It is among the most common types of cycling accidents, the League of American Bicyclists says.
For this reason, Tesla created a feature that warns occupants not to open the door because an object is approaching. The feature will sound a chime, and it will also delay the opening of the door to prevent an incident.
The release notes state (via Not a Tesla App):
“If you attempt to open a door while an approaching object is detected in your blind spot (for example, a bicyclist approaching from behind) a chime sounds, and your door will not open upon initial button press. Wait a short time and press the button a second time to override the warning.”
Tesla initially rolled out this feature back in 2024 with the Model 3 “Highland.” However, it remained with the Model 3 exclusively for over a year; that was until Tesla added it to the Cybertruck this past Spring.
Now, it is making its way to the new Model Y, 2021 and newer Model S, and 2021 or newer Model X.
The prevention of dooring incidents could eliminate many injuries to cyclists, especially in an urban setting. Dooring accounts for 10-20 percent of bike-related crashes in major cities, and over 17,000 dooring-related incidents were treated in the U.S. over the course of a decade. These usually involve fractures, contusions, and head trauma.
Tesla confirmed this morning that it has sent the first production units, manufactured with no steering wheel or pedals, to on-road testing in Austin, sharing video of the first rides with no human controls.
The lack of steering wheels and pedals in the Cybercab aligns with Tesla’s self-certification of Robotaxi as Level 4 SAE, a platform it plans to make widespread through internal vehicles and customer-owned cars that will operate and generate revenue for individuals.
The start of these engineering tests is a major signal for Tesla, which plans to bring driverless, wheel-less, and pedal-less Cybercabs to market in the coming months. With production already well underway at Gigafactory Texas, where the Cybercab is built, there is some inclination to believe the first public rides could happen sooner rather than later.
Engineering tests of the first production Cybercab have begun in Austin pic.twitter.com/fk3KQvcE8a
— Tesla (@Tesla) June 30, 2026
Tesla’s engineering tests will put the Cybercab in real-world scenarios, testing not only the hardware, but more importantly, the software that drives the car around Austin with nobody supervising it within the car.
This is perhaps the biggest part of the internal testing process, especially prior to allowing regular, everyday people to hail the Cybercab for an autonomous ride. These early rides serve as a true benchmark for Tesla: How many rides can it achieve safely? How many miles did it travel consecutively without needing an intervention? What scenarios challenge the Full Self-Driving suite the most?
The proper precautions have already been put into place as well, as Tesla released the First Responders Guide to Cybercab over the weekend, ensuring that emergency services have 24/7 access to Robotaxi Assistance, as well as other boundaries, such as Geofencing features that can be used to redirect autonomous vehicle traffic due to accidents, road closures, construction, or maintenance.
Cybercab seems genuinely close to being added to the Robotaxi fleet in Austin, but Tesla has prioritized safety throughout this entire process. Therefore, we think it could be months before it truly starts giving rides to the public. People have been frustrated with this, but Robotaxi in Austin has a tremendous safety record so far, so the slow rollout has kept people safe and accidents to a minimum.
The most important thing is that Tesla continues to show consistent progress in the Cybercab’s ramp-up toward fleet addition. A few weeks back, we saw the EPA reward the Cybercab a Certificate of Conformity, allowing it to enter the stream of commerce. Then, we saw Tesla add decals, signaling that it was likely about to start testing it publicly. That has now happened.
The next big move will be the announcement of the first rides, so this Summer should be filled with anticipation.
For years, there have been images and videos across social media platforms that have reminded me of when I was a 15-year-old kid teased by “Xbox 720” videos on YouTube. These videos are of the supposed “Tesla Phone” that Elon Musk was secretly developing in between leading Tesla with its electric cars and SpaceX with its reusable rockets.
Would you buy a Tesla phone ? pic.twitter.com/aaTwvvIJit
— Tesla Owners Silicon Valley (@teslaownersSV) October 6, 2023
Although Musk has put those rumors to bed several times, it was never completely out of the realm that he could get involved in cell phones in some capacity. Think outside the box and more macro-level, though. Instead of reinventing the computer, Musk reinvented connectivity by developing Starlink with SpaceX.
It could be something similar, TD Cowen analyst Gregory Williams said in a note last week, where he hinted SpaceX could be gathering some steam to acquire T-Mobile.
Williams said it would be the “clear choice” for SpaceX if it decided to go through with a network acquisition. He also suggested AT&T.
The move would be possible through selling more of its own stock, which would help SpaceX raise the money to purchase T-Mobile, which would cost roughly $300 billion. It could be one of the moves SpaceX makes post-IPO in terms of an acquisition: it already acquired Cursor AI for $60 billion.
Other analysts, like Dan Ives of Wedbush, believe SpaceX and Tesla will eventually merge into one anyway, and that conglomeration could come as soon as this year, some have said.
The implications of SpaceX purchasing T-Mobile are massive. A combined entity would create a truly ubiquitous network: T-Mobile’s terrestrial 5G towers and Starlink’s growing constellation of Direct-to-Cell satellites. This would essentially eliminate dead zones across the U.S. and potentially globally.
SpaceX would instantly become a full-scale facilities-based carrier with satellite differentiation; a huge advantage. This would pressure AT&T and Verizon heavily.
There are also concerns like a potential reduction in long-term competition, and of course, a deal of that size would face intense scrutiny from government agencies.
The strategic fit is compelling due to the existing Starlink–T-Mobile partnership and complementary technologies (space + terrestrial). It could create a dominant integrated communications player. However, the regulatory, financial, and execution hurdles are enormous — this remains highly speculative with no indication SpaceX is actively pursuing it right now.
Tesla expands massive safety feature worldwide in latest update
Tesla sends production Cybercab with no steering wheel, pedals to on-road testing
