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Tesla files Parallel Processing patent to reduce FSD hardware error risks

Credit: Tesla

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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:

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“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.”

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

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Joey has been a journalist covering electric mobility at TESLARATI since August 2019. In his spare time, Joey is playing golf, watching MMA, or cheering on any of his favorite sports teams, including the Baltimore Ravens and Orioles, Miami Heat, Washington Capitals, and Penn State Nittany Lions. You can get in touch with joey at joey@teslarati.com. He is also on X @KlenderJoey. If you're looking for great Tesla accessories, check out shop.teslarati.com

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Tesla Roadster’s new patent preps white-knuckle speeds, keeping it grounded

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Credit: @BLKMDL3/Twitter

Ahead of its highly anticipated unveiling, Tesla’s upcoming Roadster received a new patent that aims to keep it grounded while enabling white-knuckle speeds.

The patent, which was granted on September 29, is titled “Electric Car Fan,” bluntly stating its design but not its purpose, which is further detailed in the text of the application. Interestingly, it comes two weeks before the Roadster event, which was delayed due to unfavorable weather on Thursday, which could cause issues, as Tesla revealed the event must be held outdoors.

The purpose is to solve a problem that is relatively unique to high-performance electric cars. Instant motor torque is useless if the tires cannot plant that force, and conventional wings and underbody tunnels generate downforce only when air is already rushing past the car. At launch, in slow corners, and under hard braking from modest speed, passive aerodynamic additions contribute essentially very little to downforce.

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Tesla’s filing says that its fans can produce the downforce needed, independent of vehicle velocity, then ease off so the same hardware does not pile on drag at highway speeds, an issue that can come from excessive body modifications.

The hardware outlined in the patent is a ducted-fan package that is placed into the rear of the vehicle. An underbody inlet between the rear wheels feeds a duct that rises to a wide outlet in the diffuser. In that outlet are four axial fans, which are divided by vertical strakes. They will pull air from under the floor and press the chassis onto the pavement.

The language in the patent claims it can cut drag rather than add to it while simultaneously increasing downforce.

Tesla Roadster event requires restricted airspace, and the FAA obliges

The fans run from the high-voltage battery and a vehicle control system, so output can be modulated rather than left on as a fixed penalty.

There are additional strengths that can come from this design, like extra tire load at low speed, which can contribute to even more face-melting acceleration rates, decrease stopping distance, and sharper turn-in before a wing has air to work with. Adjustable fan speed lets the car add grip only when needed, so it can be catered to the force of a turn or acceleration.

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These designs were previously used, and banned, in some competitive settings. The Brabham BT46B was banned in F1 competition for using a similar fan design and being labeled as too effective.

Tesla still lists the Roadster as having a sub-two-second 0-60 MPH time and a 250-plus-MPH top speed, and there are expectations for a SpaceX cold-gas thruster package that could not only increase acceleration but potentially cause the vehicle to hover.

It is important to note that a patent is not a production part, and packaging four fans in a rear diffuser, managing noise, and potential debris are all things Tesla must consider. With that being said, the patent being granted shows Tesla is designing the Roadster to go fast, but it is also attempting to use unique strategies to combat any issues it might have at those speeds.

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Investor's Corner

Tesla showrooms picked clean ahead of Q3 end as demand looks strong

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Credit: @thaichiminh1907/X

Tesla (NASDAQ: TSLA) showrooms have been picked clean ahead of the end of the third quarter of the year, as demand looks to be strong and delivery estimates for new vehicles are pushed into late 2026 and early 2027.

Tesla appears to have sold out of many of its Model 3 and Model Y trim levels in the United States, as only the Model Y RWD and Model Y All-Wheel-Drive are available for delivery before the end of the year.

Additionally, many showrooms are either completely empty or void of all but just one demo unit within the buildings themselves in an effort to bolster what could be one of Tesla’s best quarters in vehicle deliveries in recent memory.

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Additionally, when I spoke to the guys at Tesla Mechanicsburg two weeks ago, when I returned the Model Y L, their third hauler of the week had just arrived, and every vehicle on it, along with every vehicle in their delivery lot, was accounted for and had a name attached to it for delivery.

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Tesla saw a 25 percent increase in deliveries in Q2 compared to the same quarter the year before. The vast majority of the 480,126 units it delivered, 467,762 vehicles to be exact, were the Model 3 and Model Y.

In Q3 2025, Tesla delivered 497,099 vehicles, once again a figure that was dominated by the company’s two mass-market vehicles. Analysts have unusually wide predictions for this quarter, likely because so many firms missed the Q2 delivery figure by such a substantial margin; Wall Street predicted 408,000 cars, while Tesla delivered 480,000.

Goldman Sachs has Tesla slotted for 435,000 deliveries in Q3, while JPMorgan said it anticipates 482,000. The median guess is about 449,000 deliveries for Q3.

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Interested in ordering a Tesla? Use my referral code for three free months of Full Self-Driving (Supervised) here.

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Lifestyle

Watch Tesla’s “guardian angel” FSD feature take over for collision evasion

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Tesla’s Automatic Collision Evasion feature can be seen in one of the first owner videos of it in action.

Tesla owner Spencer (@scotsrule08) posted on Monday that the feature “worked flawlessly,” saying FSD reengaged itself just as he was about to hit a curb. Ashok Elluswamy, who leads Tesla’s AI team, shared the clip and wrote, “A guardian angel always looking out for you.”

The video arrives in the middle of a staged rollout. Tesla first shipped Automatic Collision Evasion with FSD (Supervised) v14.3.9 in software update 2026.27.6 earlier this month, which Teslarati covered as it reached cars. Update 2026.27.10, which began going out on September 19, carried the feature improvements with FSD v14.3.10, according to release notes tracked by Not a Tesla App. The newer 2026.27.11 build is now reaching another wave of vehicles.


The feature only runs on HW4 vehicles, and it requires an active FSD purchase or subscription with both FSD (Supervised) and Automatic Emergency Braking enabled. HW3 owners receive FSD v14.2 Lite in the same updates, but that build does not include collision evasion.

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Tesla’s release notes describe two triggers. The first is an imminent frontal collision that braking alone may not prevent, in which case the car can activate FSD to steer, brake or accelerate around the hazard. That scenario is limited to highways below 85 mph, with no pedestrians or cyclists detected and no slippery road surface. The second covers a driver who appears inattentive, such as reaching into the back seat, or who seems to have switched off FSD by accident. Spencer’s curb clip appears to fall into that second category.

Tesla plans big safety improvements for Full Self-Driving v15

Once the system takes over, the accelerator is muted and light brake input will not cancel the maneuver. Drivers need to apply firm, deliberate steering force to take back control, and the car chimes to hand control back once the danger has passed.

Elluswamy recently noted that earlier hazard prediction, faster reaction time and better collision avoidance would arrive with FSD v15, the next major version.

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