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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.
Investor's Corner
Tesla gets its latest short from Michael Burry: ‘Happy it jumped back to this level’
Tesla short seller Michael Burry, the subject of the film “The Big Short,” where he was portrayed by Steve Carell, has revealed he has opened a new bet against the stock.
In a new update to his Substack newsletter in a post titled “Trading Post June 30, 2026,” Burry revealed a new set of bets against Tesla, Caterpillar, NVIDIA, Applied Materials Inc., and the iShares Semiconductor ETF.
In regard to Tesla, Burry wrote:
“And finally I shorted Tesla at 416.22. Happy it jumped back to this level.”
This means Burry likely opened his new short position after the company’s recent rally on Wall Street, which saw Tesla shares sink in mid-May, only to recover to well over the $400 mark. Currently, shares trade at around $427.
The company saw a big Tuesday as shares climbed considerably, over 10 percent. The size of the Tesla short was not provided, nor did Burry give any information on the position’s structure, the number of shares, dollar value, or whether options were used in the short.
The Tesla and SpaceX merger everyone is talking about is quietly building
Over the years, Burry has been one of the more vocal critics of Tesla, calling its share price “media inflated,” and saying it was “ridiculously overvalued” as recently as December.
The company has largely transitioned away from being known as an automotive company and instead is much more widely regarded as an AI play, mostly due to its Full Self-Driving efforts, Optimus robot development, and data collection related to both.
This has not pulled those skeptics away from being vocal about their distaste for how Tesla is valued, but there’s no denying that the company is a global force in many things, including sustainable energy, automotive, and AI.
Wedbush Securities is initiating stock coverage on SpaceX (NASDAQ: SPCX), marking the first comments on the company since it went public several weeks ago. Wedbush and its analyst handling coverage, Dan Ives, are widely bullish on fellow Musk company Tesla (NASDAQ: TSLA).
Ives wrote his first note initiating coverage of SpaceX shares on Wednesday with a $190 price target and an ‘Outperform’ rating. The firm believes the company is well positioned off of its IPO because of its wide array of projects, including AI compute power and infrastructure, connectivity projects, and launches.
“We view SpaceX as one of the most differentiated assets within the tech market with a strong footprint across its three core markets, with Starlink driving success with connectivity,” Ives wrote, “Starship launches leading to a demand flywheel and increasing deal flow for its Colossus clusters.”
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Wedbush leans heavily on Starlink, which they say is the “profitability driver given the strength of its recurring revenue base of ~12 million subscribers as of June 5th.” Ives believes Starlink is still in the “early innings” of penetrating the global telecommunications and broadband market, as it only holds less than a 1 percent share. However, this number is sure to increase over time.
It also highlights the importance of Starship, which it says is an “essential layer” of SpaceX’s overall success. SpaceX developing and displaying the ability to reuse rockets is a major cost and reliability advantage “as it reduces the necessary hardware launch costs while generating a feedback loop for future flights to improve their launch flight rate without accelerating capex spend.”
Finally, SpaceX’s recent AI/Compute projects are also very elementary, Ives writes. It is worth mentioning Wedbush said its $190 price target is derived from a valuation forecast that sees the company yielding roughly $2.48 trillion of implied enterprise value.
There are also some factors that Wedbush did not take into account with its initial coverage. The firm wrote in the note:
“We note that there is optional value coming from Starship’s accelerating scale towards sub-$200/kg unit economics, orbital data centers, and enterprise AI monetization as these factors could drive meaningful upside but these face major hurdles, so we do not take that into account with our valuation.”
SpaceX shares are down just over 2 percent today, trading at around $167 at the time of publication.
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 gets its latest short from Michael Burry: ‘Happy it jumped back to this level’
SpaceX gets initial stock coverage from Tesla’s biggest bull
