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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 Cybercab stands to gain from new rules that the Trump Administration is aiming to enforce on autonomous vehicles. On Thursday, NHTSA, under the Trump Administration’s U.S. Department of Transportation, commenced rulemaking on the Federal Motor Vehicle Safety Standards (FMVSS).
This effort aims to eliminate the mandate for manual brake pedals in vehicles that are designed to be driven exclusively by automated driving systems. This would impact the Tesla Cybercab, which the company has stated would operate without a steering wheel or pedals.
Tesla Cybercab launch is imminent after latest sighting at Giga Texas
The Trump Administration is looking to revise FMVSS No. 135, which requires standard braking systems on light-duty vehicles.
Currently, the regulation requires light-duty cars to use traditional manual braking systems that allow operators to slow the vehicle. With the advent of self-driving in the U.S., these regulations need updating, and these are the changes that could come to FMVSS No. 135:
- Removes requirements for hand- or foot-operated brake controls for vehicles designed never to be operated by a human. Existing rules still apply to AVs that retain manual controls.
- All subject vehicles must still meet the same stopping distance performance criteria via alternative testing procedures.
- While this update ensures AVs can physically stop when commanded, NHTSA is separately developing safety performance requirements for AVs in real-world driving scenarios.
- NHTSA will continue to use its broad defect enforcement authority to investigate unsafe ADS behavior and oversee recalls.
As autonomy becomes a greater part of passenger travel, these types of rule adjustments will be more than reasonable. It will give manufacturers the ability to self-certify their vehicles and avoid any red tape that could ultimately delay the deployment of these vehicles.
Administrators are also incredibly excited about the opportunity to play a role in the advancement of self-driving vehicles.
“We are at the cusp of the greatest technological revolution in vehicle technology since the innovation of the Model T,” NHTSA Administrator Jonathan Morrison said. “If we want America to lead the way, we have to reimagine our regulatory framework. That’s why under Secretary Sean Duffy’s AV Framework, NHTSA is tearing down pointless barriers to innovative designs while strengthening the fundamental safety requirements that matter and holding AV developers accountable for safe performance.”
The Cybercab entered mass production at Gigafactory Texas in April. Tesla ultimately plans to push the vehicle into its Robotaxi fleet, potentially when frameworks like these are established.
Tesla plans to boost production at its Gigafactory Berlin plant in Germany following a sharp rebound in sales and demand in Europe after a softer 2025.
The plans put Tesla in a better position to compete with strengthening companies in Europe and potentially other markets; demand indicators show Tesla is much better off than in 2025.
Last year was a tough year for Tesla in terms of overall demand in Europe. The company produced over 200,000 vehicles at the German plant last year, a soft figure compared to the 375,000 vehicles Tesla lists as its current capacity at the factory.
🚨 Tesla said this morning it will ramp up production at Gigafactory Berlin to a volume of 7,500 vehicles per week.
This is a 20 percent boost in production. Tesla will hire 1,000 new employees to help with the increase.$TSLA pic.twitter.com/kravKfRO5n
— TESLARATI (@Teslarati) June 25, 2026
Tesla’s overall European sales dropped significantly last year due to a variety of factors. However, sales are rebounding, and demand is strong once again, and only getting stronger. Tesla is now planning to bump production of Model Y vehicles at Giga Berlin upward by about 20 percent. It will also bring 1,000 new jobs to the plant.
Tesla confirmed the details of its planned production expansion in Germany this morning. It is a strategy to keep up with strengthening demand.
In Q1, Tesla saw a record 61,000 vehicles produced at Giga Berlin. European registrations rebounded sharply, with Model Y seeing 117 percent increases in March 2026 compared to last year. Germany alone saw stark increases, with a quadrupling in registrations to 9,252 units.
This trend continued in other key European markets, including France, Denmark and Sweden. Tesla registrations were up over 46 percent in some of these markets, and Model Y continued its trend as a top BEV in the market.
Demand has been recovering strongly in 2026, giving Tesla a reason to expand production efforts at the factory. These increases signal management’s confidence in sustained or growing European pull for Berlin-built vehicles.
Tesla is being sued by the family of the woman who was killed in a Texas crash involving a Model 3. The driver, who is also being sued, claimed the vehicle was operating on Autopilot mode, but Tesla executives have come out challenging that claim, stating that the driver of the vehicle overrode the system.
The lawsuit was filed by 76-year-old Martha Avila’s daughter and her husband, who allege a “design defect” involving a Tesla and a failure to warn. The suit alleges negligence against Tesla and the driver, Michael Butler.
Butler “stated he was operating with an automated driving assistance system engaged at the time of the crash,” the Harris County Sheriff’s Office said in a statement. He showed no signs of intoxication and was cooperative, the Sheriff’s Office said, according to NBC News.
Just after reports of the crash and numerous headlines that immediately blamed Tesla’s Autopilot suite, both Tesla CEO Elon Musk and Head of AI Ashok Elluswamy challenged that. Musk said the crash made “no sense” given that Tesla Autopilot and Full Self-Driving do not travel at the speeds the door cameras captured the car traveling at, which Tesla says was 73 MPH.
Tesla finally clarifies fatal Texas crash, confirms driver manually overrode acceleration
Elluswamy also revealed that Tesla data showed Butler overrode the system by pressing the accelerator to 100%, and that the pedal was compressed fully even after the car had crashed. Tesla has not released this data to the public, likely because it is communicating with agencies like the NHTSA on an investigation.
The suit uses a Washington Post analysis of government data that “identified at least 17 fatal incidents linked to Tesla Autopilot.”
This is far from the first time an accident has been blamed on Autopilot. A fatal crash in Texas was blamed on Autopilot several years ago, but when Tesla released data to the NTSB, which was investigating the crash, Autopilot was not available where the crash occurred, and Autosteer was never enabled, meaning the car was manually controlled at the time of the accident.
“Application of the accelerator pedal was found to be as high as 98.8 percent,” the NTSB said in their findings. The highest recorded speed in the five seconds leading up to the impact was 67 miles per hour. The area where the crash occurred is residential, and Texas State laws… pic.twitter.com/XGD97NHVZ2
— TESLARATI (@Teslarati) March 18, 2026
More information on the accident will be released as Tesla works with agencies to find the cause of the crash. From personal experience, it is hard to imagine Tesla Autopilot or FSD operating in this manner. It drives sometimes too cautiously in residential areas in parking lots, at least in my experience. Speeding happens, but at this rate in this type of area, it is hard to believe.
We look forward to more details being released with time.
Tesla Cybercab stands to gain from new Trump autonomy rules
Tesla plans production boost at Giga Berlin following rebound in Europe
