News
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 rolled out Full Self-Driving (Supervised) v14.3.5 yesterday, and about fifty miles of driving on the new version has given me enough time to highlight what seems to be strong about the release and what is not.
Additionally, Tesla has added a few new features with this specific update, which we’ll highlight as well.
Tesla Full Self-Driving v14.3.5 Performance
The new update is business as usual. Things seem to be running completely normal and necessary, but there are a few things that we’ve seemed to pick up on based on our own experience with v14.3.5, as well as what other users are seeing.
Initially, it seems to be more aware of its surroundings, making moves that are incredibly courteous to other drives and operating just a tad more reserved than what the suite might have done previously.
We had two instances where it showed this, the first being FSD needing to pass a Flagger Force vehicle that was placing down signage for the day. Their work truck was right at the front corner of a right-hand turn; typically where most cars travel when they take that turn.
FSD v14.3.5 recognized this, slowed down, and took the turn wide with no issues:
🚨 Tesla Full Self-Driving v14.3.5 takes a wide turn as flagger crews set up signage for the day https://t.co/3v0PL9qhlI pic.twitter.com/i4CKqxE16c
— TESLARATI (@Teslarati) July 13, 2026
Additionally, v14.3.5 backed up for a semi truck that was making a wide turn onto a road my car was on. This is not new, but it seemed to be backing up for courtesy; it didn’t seem completely necessary, but it might have put some peace of mind in the truck driver’s head:
🚨 Tesla Full Self-Driving v14.3.5 backs up for an oncoming tractor trailer taking a wide turn https://t.co/0WuAqNMpRR pic.twitter.com/s6yZGVm5Te
— TESLARATI (@Teslarati) July 13, 2026
X user Mike P, also a Pennsylvania native like myself, shared three clips of his Tesla running v14.3.5 performing similar maneuvers. He said:
“FSD turns right into a small alley that only fits one car at a time, sees oncoming car, reverses out of alley to make space, realizes oncoming car is actually parking, re-enters alley.”
Check it out here:
Rapidfire epic moments on FSD V14.3.5
1) FSD turns right into a small alley that only fits one car at a time, sees oncoming car, reverses out of alley to make space, realizes oncoming car is actually parking, re-enters alley.
2) Insane speed to vehicle cues. As FSD approaches… pic.twitter.com/bSnySSlFHR
— Mike P (@mikepat711) July 13, 2026
It seems like Speed Profiles are still in need of some tweaking; I am adjusting what Speed Profile I’m in frequently, constantly changing it to get it to travel at the correct speed. This was an issue for me on v14.3.4. It seems like they’re just a little inconsistent.
Terrible Parking
Parking attempts on v14.3.5 were not good. There are quite a few people who have said this:
Yeah it seems like FSD v14.3.5 is having some issues with parking early on https://t.co/Bw5ULfVmDq pic.twitter.com/RHdpjOEpIo
— TESLARATI (@Teslarati) July 13, 2026
David Moss, the Tesla owner who has taken multiple coast-to-coast drives without any interventions, also has had some issues with parking early on with v14.3.5:
Horrible first impression v14.3.5 on my 2025 Tesla Model 3 LR RWD Premium ðŸ˜
3 terrible parking jobs in 23 min including parking on a ramp in a business park & parking perpendicular out in the road on street only parking situation.
Wish I had a better drive but I still believe… pic.twitter.com/TtyhRHAFG7
— David Moss (@DavidMoss) July 13, 2026
New Features
Tesla has added the ability to open Camera Preview at any time. Previously, it was only available in Park. Here’s what that feature looks like in action:
🚨 Here’s the new Camera Preview feature on FSD v14.3.5 pic.twitter.com/OodfZgDppy
— TESLARATI (@Teslarati) July 13, 2026
Check back later this week for a longer review of what we’ve noticed on Full Self-Driving v14.3.5.
Lifestyle
Tesla makes the cut on California’s newest EV Rebate program
California just signed a $270 million EV rebate into law and it starts this summer.
California Governor Gavin Newsom signed SB 168 into law on Monday, July 13, 2026, creating a $270 million EV rebate program that delivers money directly at the dealership rather than as a tax credit applied months later. The program, called MyFirstEV, is funded equally by California’s state budget and participating automakers, with each contributing $135.5 million to make the math work.
The timing is directly tied to the loss of federal support when the $7,500 federal EV tax credit ended, removing the most significant consumer incentive that had driven EV adoption in the U.S. California, which accounts for roughly one-third of all EVs sold nationally, moved to fill that gap with a state-level replacement.
The rebate structure is straightforward. First-time EV buyers can receive $3,500 off any new battery-electric vehicle with an MSRP up to $50,000. Used EVs priced at $25,000 or below qualify for a $1,750 rebate. The credit is applied at the point of sale, which removes the friction of the old federal system where buyers had to wait for tax season to see the benefit. The program goes live later this summer, with the California Air Resources Board expected to release full participation details next month.
California hits Tesla Cybercab and Robotaxi driverless cars with new law
For Tesla buyers, the implications are mixed. The Tesla Model 3 RWD at $42,490 and the Model 3 Long Range at $47,490 both fall under the $50,000 cap and would qualify for the full $3,500 rebate for first-time buyers. The Model Y, which starts at $44,990 after Tesla’s recent price adjustment, also qualifies. The Model X, Model S, and Cybertruck all exceed the cap and receive no benefit. As Teslarati has reported, the program also includes a carve-out exempting California-based automakers like Rivian and Lucid from the price cap entirely, a provision that puts Tesla at a disadvantage since it relocated its headquarters to Texas in 2021.
Other qualifying vehicles include the Chevrolet Equinox EV, Ford Mustang Mach-E, Hyundai Ioniq 5, Kia EV6, and Volkswagen ID.4.
The Tesla Semi is entering a new Pilot Program with Paper Transport, LLC (PTI), a Wisconsin-based transportation provider. The company will test the Semi’s Long Range configuration through “dedicated operations within the Chicago market.”
Chicago presents an interesting challenge for the Semi, as it will be a colder-weather climate that will test the Semi’s ability to operate in lower temperatures and in potentially large accumulations of snow. This is something Tesla has been testing with the Semi in Alaska and even in Northern California during the colder months, but Chicago will present a truly tough midwestern winter.
Tesla Semi spotted on journey home after winter performance testing
PTI says it is using the Semi to evaluate its strategy of reducing transportation emissions while maintaining performance, reliability, and cost efficiency. These are major arguments for the Semi being introduced into new fleets.
CEO of PTI Tyler Ellison said:
“PTI has been a leader in sustainable transportation solutions for over 15 years. We take a consultative approach to helping customers identify and implement the right transportation solution for their network. Our partnership with Tesla expands our portfolio alongside renewable natural gas and intermodal, giving customers more ways to reduce Scope 3 emissions without compromising service or economics.”
PTI is far from the first company to adopt the Semi within a fleet, as Tesla entered strategic agreements with PepsiCo. and its subsidiary Frito-Lay for a Pilot Program that extended throughout the California region.
Tesla has let companies like those utilize the Semi to determine whether it would be suitable for their operations. Additionally, Tesla gets valuable information regarding the Semi’s performance, knowing what to improve and what is ideal for companies that will utilize the all-electric truck for regional and nationwide logistics.
PTI plans to utilize the Long Range configuration, which is priced at $290,000 and features a range of approximately 500 miles, a three-motor powertrain, up to 800 kW of drive power, and consumption of just 1.7 kWh per mile.
Tesla Semi pricing revealed after company uncovers trim levels
VP of Maintenance at PTI, Bryan Ellen, added:
“We are excited to partner with Tesla, leveraging their ever-evolving technology. We are bullish in our estimation of the parallels available between our dedicated model and the efficiency of their fully electric Class 8 tractor. We anticipate a growing synergy between our businesses as we work to facilitate this sustainable solution for our customers.”
PTI has logged more than 87 million miles using sources like compressed and renewable gas, but now is looking to take it a step further with fully electric operations.
Tesla Full Self-Driving v14.3.5 Early Impressions: new features and early performance
Tesla makes the cut on California’s newest EV Rebate program
