Tesla has filed a new patent for “Parallel Processing System Runtime State Reload,” comprising of a system of three or more processors working in conjunction to effectively eliminate the possibility of hardware failure during the use of Autopilot or Full Self-Driving. The patent outlines a robust system of parallel processors that can operate in the event that one of them fails or experiences a runtime state error. “Should one of the parallel processors fail, at least one other processor would be available to continue performing autonomous driving functions,” the patent shows.
The patent was filed and published on August 26th and comes just a week after the company’s Artificial Intelligence Day event that was held last Thursday. Outlining a system of at least three processors operating in parallel, it is monitored by circuitry and can locate and identify if one of the three parallel-operating processors is having a runtime state error. The circuitry will then identify a second processor to switch to in the event of a runtime error, access the runtime state of the second processor, and load the runtime state of the second, operational processor into the first processor, which is experiencing a runtime error.
(Credit: Tesla)
Tesla describes the patent in detail:
“A system on a Chip (SoC) includes a plurality of processing systems arranged on a single integrated circuit. Each of these separate processing systems typically performs a corresponding set of processing functions. The separate processing systems typically interconnect via one or more communication bus structures that include an N-bit wide data bus (N, an integer greater than one). Some SoCs are deployed within systems that require high availability, e.g., financial processing systems, autonomous driving systems, medical processing systems, and air traffic control systems, among others. These parallel processing systems typically operate upon the same input data and include substantially identical processing components, e.g., pipeline structure, so that each of the parallel processing systems, when correctly operating, produces substantially the same output. Thus, should one of the parallel processors fail, at least one other processor would be available to continue performing autonomous driving functions.”
Technically speaking, the autonomous vehicle needs only one processor to function as described in an accurate fashion. However, these processors can be overloaded with data when loading into the Neural Network and could experience short-term and non-permanent operational errors. When this occurs, the system would then switch to one of the other processors for normal operation, with at least two backup processors in this patent, as it repeatedly mentions a series of three.
Tesla details its self-driving Supercomputer that will bring in the Dojo era
The second processor would then activate and load the runtime state into the first processor to make the primary processor chip operational once again:
“Thus, in order to overcome the above-described shortcomings, among other shortcomings, a parallel processing system of an embodiment of the present disclosure includes at least three processors operating in parallel, state monitoring circuitry, and state reload circuitry. The state monitoring circuitry couples to the at least three parallel processors and is configured to monitor runtime states of the at least three parallel processors and identify a first processor of the at least three parallel processors having at least one runtime state error. The state reload circuitry couples to the at least three parallel processors and is configured to select a second processor of the at least three parallel processors for state reload, access a runtime state of the second processor, and load the runtime state of the second processor into the first processor.”
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The purpose of this patent is to continue system availability, even when the primary processor is experiencing functionality issues due to overuse. The two additional processors essentially act as “backup” and can determine whether autonomous driving systems are meant to be enabled if the first processor experiences an error. “With one particular example of this aspect, the parallel processing system supports autonomous driving and the respective sub-systems of the at least three parallel processors are safety sub-systems that determine whether autonomous driving is to be enabled.”
FIG. 13 is a timing diagram illustrating clocks of the circuits of FIGS. 8 and 10 according to one or more other described embodiments. As shown, the runtime state (data1) of first processor/first sub-system is determined to have at least one error. In response to this determination by the state monitoring/state reload circuitry, the signal st_reload1 is asserted to initiate the loading of runtime state (data2) from second processor/second sub-system into the first processor/first sub-system. With the embodiment of FIG. 13, a first clock (clk1) is used for the first processor/first sub-system and a second clock (clk1) is used for the second processor/second sub-system. There exists a positive skew between the first clock (clk1) and the second clock (clk2), resulting in a late cycle of the loading of the runtime state (data2) of the second processor/second sub-system into the first processor/sub-system, potentially resulting in errors in the runtime state reload process. (Credit: U.S. Patent Office)
It also appears that this patent aligns with Tesla CEO Elon Musk’s previous description of the Dojo self-driving Supercomputer, which was detailed at AI Day. To increase the accuracy and encourage the parallel operation of the processors, the system will utilize a clock input to calibrate the two processors, increasing the accuracy of the system.
Tesla has focused on accurate FSD operation and has revised its strategy on several occasions. After moving to a camera-only approach earlier this year for the Model 3 and Model Y, the company is experiencing more accurate FSD operation through the harmonized processing of its eight exterior cameras. The operation of internal processors, which are responsible for compiling, compressing, and sending data to the Neural Network, can fail temporarily, so the presence of backup processors to continue comprehending self-driving data is a positive idea.
The full patent is available below:
Tesla Patent Parallel Processing System Runtime State Reload by Joey Klender on Scribd
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.
🚨 Tesla looks to have installed Camera Washers on the side repeater cameras on Robotaxis in Austin
pic.twitter.com/xemRtDtlRR— TESLARATI (@Teslarati) January 23, 2026
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.
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:
Tesla has finally turned off the blinker/turn signal noises in their Model Y Robotaxis.
This is a small update, but will definitely be noticeable for riders. It didn’t really make much sense to leave the turn signal sound on when it’s Unsupervised. pic.twitter.com/ITwx60PAMO
— Sawyer Merritt (@SawyerMerritt) July 27, 2026
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.
I kind of like it being on, threw me off when riding with Zoox who has had it disabled
— Dan Burkland (@DBurkland) July 27, 2026
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.
Tesla released Full Self-Driving version 14.3.6 last week, and after what was potentially one of the best FSD releases in v14.3.5, there has been a bit of a regression. While there are some bright spots, the changes made to v14.3.6 seem to have backtracked some behaviors.
Overall, it is hard to really complain about FSD in any sense; it has revolutionized how I travel literally anywhere. According to my self-driving app, the last time I went a day without using it was 59 days ago.
However, I think it’s also important to recognize when things are just plain bad with FSD. There are times it does truly mind-boggling things, and I’ll dive into those here. Additionally, I only had these issues on local roads, not on highways. Highway operation, generally, is always incredible other than the occasional complaint about speed or left lane camping.
With those things being said, my personal experience may not represent others’ experiences. A handful of people have said they have had a similar experience on v14.3.6, while others have said it is more than normal.
Turning Hesitancy, Inaccuracy
I’ve noticed more inaccuracy turning into multi-lane stretches of road than in any version I can remember. I’ve had at least three instances of FSD turning into a stretch of roadway that has two or more lanes, and not selecting a lane confidently as it has in past versions.
I think Tesla FSD v14.3.6 is a regression from previous .3 branches
This version in particular has been incredibly hesitant, jerky, and indecisive at times. There’s actually been two drives that I have decided to not used FSD for the remainder of the trip. These were local trips… pic.twitter.com/YobHDOKRS6
— TESLARATI (@Teslarati) July 26, 2026
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Instead, the car will drive over one of the dashed road lines, and the steering wheel will jerk back and forth before picking the lane. It should be said that it has always picked the correct lane when choosing based on the navigation, but it is still very indecisive. The steering wheel jerking is reminiscent of some of the later versions of v13.
I admit I really hate to see the steering wheel jerking come back. However, I think when Tesla releases v14.3.7, it won’t be present. When there are occurrences of it in FSD versions, it is usually resolved by the following release.
FSD Disregards Manual Turn Signals
This is my biggest bone to pick with FSD other than Navigation issues, but this one seems like it would be such an easy fix.
If Tesla is going to put the word “Supervised” on the end of “Full Self-Driving,” then when I tell the car to do something, it should do it. If I input an increase in speed by pressing the accelerator, the car will immediately respond. It does not disregard my input because it feels it is traveling at the right speed.
FSD should never disobey and turn off turn signals that the driver inputs. Trying to direct the car into the correct lane, I had initiated the left turn signal not once, not twice, but three times, with the car turning it off all three times and continuing in a lane that would end in just one block. The only solution at this point would be to zipper merge.
This goes back to the fact that self-driving’s biggest bottleneck might be rider preference. A zipper merge might have been more than reasonable, might have saved me time that I spent sitting through an additional light cycle, and might be something many drivers would do. I was in no hurry, I traditionally do not try to zipper merge because it feels inconsiderate, and lastly, the car should have just followed my input.
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This caused me to disengage and drive manually the rest of the way home. Sometimes I just do not need FSD to try to pass every car it can at intersections.
Bird Braking is a Thing of the Past
The big complaint with recent versions of Full Self-Driving has been what we’ve coined as “bird braking,” which is when the car will brake suddenly as a bird flies past.
There have been zero issues with this so far in v14.3.6, which is an excellent improvement.
FSD Might Already Be Taking Note of Driver Preferences
Another thing I have noticed over the past few days is that v14.3.6 seems to already be taking my preferences with navigation into account.
This is something that is supposed to be rolling out with the Summer Update, but I have a hunch it’s already present and might have been included in this v14.3.6 build. On Friday, FSD pulled into an entrance to a local convenience store that it had never attempted to go into before.
Typically, I manually pull into this entrance because it avoids heavy cross traffic at the main entrance. FSD has always chosen that congested main entrance.
I don’t want to get anyone excited but my Tesla running FSD v14.3.6 just:
✅ Pulled into an entrance at my local Sheetz that I routinely pull into manually but FSD never has entered
-✅ Pulled into my assigned parking space at home despite many other spots being vacant https://t.co/ZUShvknTWO pic.twitter.com/83O5a2S0eh
— TESLARATI (@Teslarati) July 24, 2026
Additionally, FSD has pulled into my assigned parking spot at my townhouse community on multiple occasions with this release. This is something that used to happen ocassionally, but not consistently.
It also navigated back to the same convenience store last night, drove through crazy cars scrambling to gas pumps, navigated out of the parking lot correctly, drove me home, and, once again, parked in my assigned spot.
As previously stated, this release just seems to have a few things that need to be brought to Tesla’s attention, and also to make others who use FSD aware of some things that I’ve experienced. I look forward to the next release that will remedy these issues, just as Tesla has always done in the past.
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Tesla briefly offered this Robotaxi part for your personal car
Tesla Robotaxi gets sweeping but polarizing change
