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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.

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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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Tesla Model Y L gets biggest hint yet that it’s coming to the U.S.

Over the past week, a noticeable wave of American Tesla influencers descended on China and Australia, each posting in-depth YouTube reviews of the Model Y L within days of one another.

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Credit: Tesla China

The Tesla Model Y L is perhaps the most wanted vehicle in the company’s lineup in the United States, especially now that it is void of a true family vehicle with the removal of the Model X.

In China, Tesla currently offers a longer, more family-friendly version of the Model Y, known as the Model Y L, which is longer in terms of its wheelbase and larger in terms of interior space, making it the perfect option for those with a need for a tad more room than what the all-electric crossover offers in its Standard, Premium, and Performance trims.

However, there seems to be a hint that the Model Y L could be on its way to the United States. Over the past week, a noticeable wave of American Tesla influencers descended on China and Australia, each posting in-depth YouTube reviews of the Model Y L within days of one another:

The timing has sparked some intense speculation as to whether Tesla is quietly preparing to bring the long-wheelbase, three-row family SUV to North America after months of requests from fans.

The Model Y L stretches the wheelbase by about five inches compared to the standard Model Y.

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This delivers dramatically more rear legroom, optional captain’s chairs in the second row, and a true six- or seven-seat configuration ideal for growing families. Reviewers praise its refined ride, upgraded interior features like a rear touchscreen and premium audio, and competitive range—up to roughly 466 miles in some configurations.

Many observers see the coordinated influencer trip as more than a coincidence. Tesla China appears to have hosted the group, possibly tied to the Beijing Auto Show, giving U.S.-focused creators early access to hands-on footage aimed squarely at North American audiences.

Tesla Model Y lineup expansion signals an uncomfortable reality for consumers

Tesla watchers are quick to point out this isn’t the first time such a pattern has emerged.

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Just months earlier, American influencers were similarly invited to China to test-drive the refreshed Model Y Performance. Those videos dropped in the lead-up to the variant’s U.S. rollout, generating exactly the kind of pre-launch hype that helped smooth its September arrival in American showrooms.

The parallel is obviously hard to ignore, as Tesla has used overseas influencer trips before as a low-key way to build anticipation without formal announcements. With the Model Y L potentially hitting the U.S. market late this year, according to CEO Elon Musk, the timing would make sense.

Tesla Model Y L might not come to the U.S., and it’s a missed opportunity

Of course, it could still be coincidental. Tesla regularly invites creators to its Shanghai factory and events for broader promotional purposes, and the Model Y L has been on sale in China for some time. No official word has come from Tesla or Elon Musk about U.S. availability, pricing, or timing.

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Import tariffs, regulatory hurdles, and production priorities at Fremont or the new Mexican Gigafactory could still delay or alter any stateside plans.

Even so, the buzz is real. U.S. families have long asked for a more spacious, three-row Tesla SUV that doesn’t require stepping up to the larger Model X.

If the influencer campaign is any indication, the Model Y L—or a close North American cousin—could finally answer that call. For now, American Tesla fans are watching closely and wondering whether this latest China trip is just good content… or the opening act for something much bigger stateside.

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Tesla begins probing owners on FSD’s navigation errors with small but mighty change

Previously lumped under “Other,” these incidents made it harder for Tesla’s AI team to isolate and prioritize map-related issues in their reinforcement learning models. There was a lot of disagreement on how certain interventions should be reported.

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Tesla has started probing owners on how often its Full Self-Driving suite has Navigation errors with a small but mighty change last night.

In its latest Software Update, which is Version 2026.2.9.9 featuring Full Self-Driving (Supervised) v14.3.2, Tesla has introduced a targeted improvement to how owners will report interventions.

With the initial rollout of v14.3.2, Tesla introduced a new Intervention Menu that appears when a disengagement occurs. It allowed owners to choose from four different categories: Preference, Comfort, Critical, or Other.

Tesla has voided the Other option and replaced it with a new “Navigation” choice, which seems much more ideal given the complaints owners have had about navigation. This seemingly minor UI tweak, rolled out widely in recent days, marks another step in Tesla’s ongoing effort to refine its autonomous driving stack through precise, crowdsourced data.

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Tesla made this change in direct response to longstanding community feedback. For years, FSD users have noted that navigation errors—such as incorrect speed limits, suboptimal routes, or directing the vehicle to a building’s rear entrance instead of the main one—frequently force interventions.

Previously lumped under “Other,” these incidents made it harder for Tesla’s AI team to isolate and prioritize map-related issues in their reinforcement learning models. There was a lot of disagreement on how certain interventions should be reported:

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By adding a dedicated “Navigation” label, the company can now tag disengagements more accurately, feeding cleaner data into its neural networks. This supports faster iteration on routing algorithms, map accuracy, and intent-aware navigation.

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Community consensus around Tesla’s navigation system has been consistent and candid. While the end-to-end AI driving behavior in v14.x earns widespread acclaim for smoothness and safety, navigation remains FSD’s clearest Achilles’ heel.

Owners frequently cite outdated map data, failure to learn from repeated corrections, and routing decisions that feel less intuitive than Google Maps or Apple Maps. Common complaints include phantom speed-limit changes, inefficient local roads, and poor point-of-interest handling.

Tesla Summon got insanely good in FSD v14.3.2 — Navigation? Not so much

Many drivers report intervening on navigation far more often than on core driving maneuvers, with some estimating it accounts for the majority of disengagements outside of edge cases.

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Long-term users note that the same mapping glitches persist across years and software versions, despite thousands of collective miles of feedback. Yet the addition of the “Navigation” option has been met with optimism. It signals Tesla’s commitment to data-driven progress and suggests navigation improvements could arrive sooner.

For a community that already logs millions of FSD miles monthly, this small change could unlock meaningful gains in reliability and user trust—potentially accelerating the path to unsupervised autonomy.

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Tesla expands Robotaxi in a way that was long anticipated

Instead, it has to do with the consumer base it offers Robotaxi to, because it has not offered it to everyone in the past.

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Credit: Grok Imagine

Tesla has expanded Robotaxi in a way that was long anticipated, and it does not have to do with a new, larger geofence in a city where it already offered its partially autonomous ride-hailing suite, or a new city altogether.

Instead, it has to do with the consumer base it offers Robotaxi to, because it has not offered it to everyone in the past.

Tesla has taken a major step forward in its autonomous ride-hailing ambitions with the official launch of the Tesla Robotaxi app for Android users. Released on the Google Play Store on April 24. Titled simply “Tesla Robotaxi,” the app is now available to download directly from Tesla.

This rollout fulfills a long-anticipated expansion that opens the service to hundreds of millions of Android smartphone users who were previously unable to access it on iOS alone.

The app delivers a streamlined, driverless ride experience powered by Tesla’s automated driving technology.

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Users sign in with a Tesla Account, view the current service area map within the app, enter a destination, and receive an estimated fare and arrival time before confirming the ride. When a Model Y from the Robotaxi fleet arrives, riders confirm the license plate, enter the vehicle, fasten their seatbelt, and tap “Start Ride” on either the app or the vehicle’s touchscreen.

During the trip, passengers have access to all the same controls that iOS users do, and can adjust climate settings, seat positions, and music while tracking progress on an in-app map. The interface also allows drop-off changes or support requests if needed. After the ride, users exit, close the doors, and submit feedback.

This Android availability directly broadens the rider base for Robotaxi in its initial service areas. Unfortunately, Android users are used to being subject to delayed launches of new features available to Tesla owners.

By removing the iOS-only barrier, Tesla instantly expands the addressable market, enabling far more people to summon and use the autonomous vehicles already operating on public roads.

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The move is a foundational requirement for scaling ride volume and gathering the real-world data needed to refine the unsupervised Full Self-Driving system that powers every trip.

For the Robotaxi program itself, the launch signals steady operational progress. It prepares the service for higher utilization rates as the fleet grows and supports the transition from limited early deployments to a more robust network.

Tesla expands Unsupervised Robotaxi service to two new cities

Tesla has indicated that users outside current service areas can sign up at the company’s website for future notifications, pointing to a deliberate, phased geographic rollout.

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Looking ahead, the company plans to incorporate Cybercab vehicles to increase fleet capacity and efficiency while continuing to expand service territories. With the Android app now live, Tesla has removed a key adoption hurdle and positioned Robotaxi for the next phase of growth in autonomous urban transportation.

The infrastructure is now in place to support significantly larger rider demand as production and deployment accelerate.

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