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Tesla files Parallel Processing patent to reduce FSD hardware error risks

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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.

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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.”

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.”

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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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Texas man charged in fatal Tesla crash where he blamed Autopilot

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A Texas man has been arrested and charged with manslaughter after his Tesla crashed into a home last month, striking a woman inside and killing her. The driver, Michael Butler, claimed the vehicle was in self-driving mode, but information from Tesla shows that Butler overrode the system.

Butler was arrested on Wednesday and booked at the Harris County, Texas, jail. He remained in custody through Thursday and Friday; he did not enter a plea, and his next court hearing is scheduled for Monday.

Tesla finally clarifies fatal Texas crash, confirms driver manually overrode acceleration

There are a handful of new clues in the case that could clear Tesla of any wrongdoing, especially as the woman who was killed’s family, the Avilas, filed a wrongful death lawsuit against Tesla and Butler, seeking at least $1 million in damages.

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Charging documents from the Harris County prosecutor now show that Butler, who was working DoorDash the evening of the accident, had been using Full Self-Driving mode without incident through the duration of multiple deliveries that evening.

In the moments leading up to the crash, while in FSD and approaching a left turn, Butler pressed the accelerator pedal, overriding FSD’s speed control, and continued to push it until it reached 100 percent. This caused rapid acceleration; the brake pedal was never pressed, and there is no data to show that Butler aimed to turn away from the curb or house.

The charging documents state:

“I noted that the brake pedal was never pressed in the final minute before the crash. I also did not see any data to indicate that the driver attempted to turn away from the curb that he eventually struck. Further, I observed that no mechanical error was detected or recorded by the vehicle before BUTLER and the Tesla struck the curb.”

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Additionally, a forensic analysis of Butler’s phone showed that he searched Google around the time of the crash with queries questioning why FSD was “too timid,” “not aggressive enough,” and even searched, “FSD is not aggressive enough for city driving.”

The documents outlined this:

“Investigator Veal also informed me that he had received BUTLER’s cell phone from Deputy Amad and that HDAO digital forensics team had completed a data extraction and download of the phone. Multiple Google searches related to Tesla had been made from BUTLER’s phone in the months leading up the crash. I noted multiple searches in May of 2026 indicating an apparent frustration with Tesla’s FSD mode, including the following searches: “Tesla fsd not aggressive enough 2026 model,” “Tesla fsd not [sic) aggressive enough 2026,” “FSD is not aggressive enough for city driving,” and “tesla fsd too timid.”‘

Tesla had claimed just after the crash that its internal data showed Butler had overridden the system’s speed control and pressed the accelerator completely, causing the vehicle to travel at an excessive rate of speed. Eventually, the car slammed into Avila’s house, killing her.

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Butler has now been formally charged with Manslaughter, a felony.

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Tesla’s strong Q2 deliveries: Four key drivers behind the surprise

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(Credit: Tesla)

Tesla shocked with its quarterly delivery report yesterday by reporting it delivered 480,126 vehicles in the second quarter of 2026, a 25 percent year-over-year jump that crushed Wall Street estimates of roughly 400,000–408,000 units. Production reached 451,758, with Model 3 and Model Y accounting for the vast majority.

The result ended two years of annual delivery declines and drew down inventory, signaling demand that outpaced earlier production.

Tesla bears had long warned that the expiration of the U.S. federal EV tax credit would hammer demand. Without the $7,500 incentive, they argued, American buyers would balk at higher effective prices, leading to a sharp slowdown.

Will Tesla thrive without the EV tax credit? Five reasons why they might

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That narrative has not played out as predicted. While U.S. EV sales faced broader headwinds, Tesla’s global numbers held firm, underscoring the company’s ability to offset domestic pressure through other levers.

There are several plausible factors that explain Tesla’s strength during this quarter. Let’s take a look at them:

Rising Gas Prices

Rising gas prices provided a powerful tailwind, especially in the U.S.

Geopolitical tensions tied to the Iran conflict pushed fuel costs higher earlier in the year, amplifying the lifetime savings of electric vehicles. Even as oil prices later moderated, the psychological and financial impact lingered, encouraging fleet operators and private buyers to accelerate EV purchases. European sales rebounded sharply, helping drive the quarter’s outperformance.

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Full Self-Driving Adoption

Advances in Full Self-Driving (FSD) supervised software also appear to have boosted appeal. Tesla expanded FSD availability in select European markets and continued refining the system.

For tech-oriented buyers, the promise of future autonomy and enhanced driver-assistance features adds perceived value beyond the car itself. This differentiation helps Tesla stand out in a crowded market where competitors focus primarily on hardware and basic range.

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Pricing Strategy, Affordable Configurations

Tesla’s offerings and its pricing strategy during Q2 further stimulated demand. Tesla introduced lower-cost versions of the Model 3 and Model Y, widening accessibility without sacrificing core margins.

These moves countered affordability concerns and attracted buyers who had been waiting on the sidelines. Combined with attractive financing and leasing options, the pricing strategy converted interest into actual orders more effectively than many analysts expected.

Broad European Recovery

Supported by government incentives, corporate fleet electrification, and easing political headwinds around CEO Elon Musk, Tesla was supplied additional momentum through stronger registration numbers throughout Europe.

Strong exports from the Shanghai Gigafactory and a production ramp at Giga Berlin ensured supply met this resurgent demand. Corporate buyers, in particular, accelerated transitions to EVs to meet sustainability targets, providing a steady volume base.

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These elements created a virtuous cycle that delivered the strong deliveries report. While bears correctly flagged the loss of the U.S. tax credit as a risk, Tesla’s diversified playbook demonstrated that it could remain resilient against those headwinds. The Q2 beat suggests the company remains adept at navigating shifting market conditions, even as competition intensifies.

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Tesla Semi involved in first known fatal crash in Nevada

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Credit: Tesla

A Tesla Semi was involved in a fatal collision on U.S. Highway 50 in Dayton, Nevada, on Sunday, June 28, 2026, marking the first known fatal crash involving the electric Class 8 truck. The incident occurred around 7:20 a.m. at the intersection with Traditions Parkway, approximately 40 miles east of Reno and close to Tesla’s Gigafactory Nevada.

According to the Lyon County Sheriff’s Office and the Nevada State Police Highway Patrol, a semi-truck struck two passenger vehicles stopped at a traffic signal. The truck hit the vehicles from behind. Two people were pronounced dead at the scene, and a third person suffered life-threatening injuries and was flown to a hospital, Forbes reported.

Preliminary statements gathered at the scene by the Lyon County Sheriff’s Office suggested the truck driver may have fallen asleep at the wheel. However, the Nevada Highway Patrol, which is leading the investigation, stated that the official cause has not yet been determined.

Additional information is expected to be released early the following week. The truck was seized for evidence as part of the ongoing probe.

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Responders at the scene included deputies from the Lyon County Sheriff’s Office, personnel from the Nevada Highway Patrol, Central Lyon County Fire Department, and the Nevada Department of Transportation. The crash led to the temporary closure of U.S. 50 in both directions.

The Tesla Semi is Tesla’s battery-electric heavy-duty truck, produced at the nearby Gigafactory in Nevada. Authorities initially described the vehicle as a semi-truck; its make was subsequently confirmed through reporting and scene identification; an interesting bit of information here, as the Semi is not yet available publicly and many do not know that Tesla builds electric trucks.

The investigation remains active, with no further official details on contributing factors or vehicle systems released as of early July 2026.

This incident highlights ongoing scrutiny of commercial vehicle safety on Nevada highways, particularly involving fatigue. Law enforcement continues to gather evidence and witness statements.

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