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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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.”
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
News
SpaceX just locked up a NASA record no other U.S. spacecraft can touch
SpaceX’s Crew-13 Dragon reached the ISS in under eight hours, and NASA confirmed a record.
SpaceX now owns every spot on the list of the five fastest trips a U.S. spacecraft has ever made to the International Space Station, and its newest entry beat the old mark by more than four hours.
Crew Dragon Grace docked to the forward port of the station’s Harmony module at 7:05 p.m. ET on October 1, just 7 hours and 55 minutes after lifting off from Space Launch Complex 40 at Cape Canaveral. NASA confirmed the milestone in a space station blog update, writing that the flight “marked the fastest launch‑to‑docking of a U.S. spacecraft in the history of the International Space Station.”
The previous U.S. record also belonged to Dragon. SpaceX’s uncrewed CRS-31 cargo mission reached the station in a little over 12 hours in November 2024. The fastest crewed trip before last week was Crew-11, which took 14 hours and 43 minutes in August 2025, according to Space.com.
A post that Elon Musk reposted on Monday filled out the rest of the ranking. Behind Crew-13, CRS-31 and Crew-11 sit Axiom’s Ax-2 mission at 15 hours and 35 minutes and NASA’s Crew-4 at 15 hours and 44 minutes. All five flew on Dragon.
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Crew-13 carried NASA astronauts Jessica Watkins and Luke Delaney, Canadian Space Agency astronaut Joshua Kutryk, and Roscosmos cosmonaut Sergey Teteryatnikov. NASA had projected a docking around 8 p.m. ET, as Teslarati reported the day before launch, and Dragon arrived nearly an hour early. Our launch day coverage noted that the flight was lined up to be the quickest Crew Dragon transit yet.
The speed came from timing more than hardware. SpaceX’s Julianna Scheiman said the station “was in an opportune spot in space,” which let Dragon start closing the gap almost immediately after reaching orbit. “This is close to the fastest it could be,” she added. Most Crew Dragon flights still take close to a day, using a series of Draco thruster burns to raise and phase their orbit before arrival.
Dragon’s next job at the station is a departure. NASA said Monday it is targeting 8:05 a.m. ET on Wednesday, October 7, for Crew-12 to undock, setting up a splashdown off the coast of California around 11:34 a.m. on Thursday. Clearing that port makes room for CRS-35, a cargo Dragon carrying the final set of iROSA solar arrays.
Dragon remains NASA’s only operational ride to the station while Boeing’s Starliner stays grounded, and the agency recently added Crew-15, Crew-16 and Crew-17 to SpaceX’s contract in a $946 million modification.
Elon Musk has acknowledged that early discussions with Taiwan Semiconductor Manufacturing Company (TSMC) could bring the company into his ambitious Terafab semiconductor project, signaling a possible partnership with the world’s leading contract chipmaker.
Musk confirmed that early talks are underway, but as of right now, they are “just discussions.” There is no confirmation of a deal nor dismissal of the possibility of one, leaving open the prospect of one of the largest advanced-chip collaborations under discussion in the U.S.
@wholemars Just discussions, but something may come of it
— Elon Musk (@elonmusk) October 3, 2026
The report that speculated on potential discussions between Terafab and TSMC comes from Tim Culpan, who outlined a few ways the collaboration could operate. One is TSMC using the project as an “anchor customer” for future facilities in Texas, potentially contributing process expertise, operational know-how, or capacity while Terafab provides capital, long-term purchase commitments, or both.
Tesla and SpaceX jointly developed the Terafab project, with Intel already participating on the tech side. Elon Musk announced the project in March, and it intends to produce more than one terawatt of AI compute capacity annually once fully built.
Company statements place the first phase at approximately $16.8 billion in cost, with later filings pointing to a total that could reach well into the tens of billions across multiple stages.
Intel joined the effort in April 2026 and is expected to supply its 14A manufacturing process for the full-scale plant.
Musk has said existing suppliers, including Samsung and TSMC, remain important for near-term needs; Tesla already has production arrangements with Samsung for AI5 and AI6 chips, but that future demand from Optimus robots, Cybercab vehicles, and planned space-based data centers will eventually exceed what the global industry can currently deliver.
Terafab is positioned as the long-term answer to that projected shortfall, and Tesla did something similar during COVID to avoid a chip shortage. This is just a much larger-scale solution.
If the partnership were to materialize, it would add TSMC’s industry-leading strategies to a project that already combines Tesla’s and SpaceX’s capital and offtake with Intel’s process technology. For now, the only public confirmation is Musk’s brief acknowledgement that conversations are occurring.
Tesla’s early strategy for charging units operating within its Robotaxi fleet reveals that the company surely has not lost any of that scrappy DNA that took it from an unlikely success story to the most valuable carmaker in the world.
An observer at a Tesla Supercharger in Austin spotted ten total Robotaxi vehicles arrive: one Cybercab and nine Model Y units. A Tesla employee was waiting at the lot and allowed each unit to park itself; every car that arrived had nobody in it.
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The Tesla employee would walk around and plug each car in, adjusting the parking if needed:
So look at what I found. This is how Tesla charges unsupervised robotaxis at a public supercharger. Here is a driverless Cybercab showing up with no one in it. There are 9 other Model Ys that showed up too. A Tesla employee is walking around and plugging each of them in. She also moves the cars if they are not positioned well enough to charge. I love this process. One person charges multiple robotaxis at once
— Abhimanyu Yadav (@WorldlyReviewer) October 3, 2026
It’s a very interesting strategy, but extremely understandable at this early point in the Robotaxi program. It’s only been out for about 15 months, and Cybercab just entered the fleet in early September.
On top of that, Tesla is still working tirelessly on its wireless charging apparatus, and a new patent was just published regarding that product last week.
However, this is just another example of how Tesla still has plenty of that scrappy DNA leftover from the “production hell” days, when CEO Elon Musk slept on the floor of the factory, employees were working crazy hours, Tesla was building Sprung Structures to build cars in, and the company was tiptoeing on the brink of bankruptcy.
@Teslarati Sheer magnitude of the entire production system is hard to appreciate. Almost every element of production is >75% automated. Only wire harnesses & general assembly, which are <10% of production costs, are primarily manual.
— Elon Musk (@elonmusk) October 12, 2020
For now, Tesla is utilizing a simple system for recharging its ride-hailing vehicles, and that is a Tesla employee doing it manually until another solution presents itself. Sure, it’s not the most high-tech thing, and it certainly is not what people might have expected at this point in time, but it works, and it’s keeping the entire suite running.
SpaceX just locked up a NASA record no other U.S. spacecraft can touch
Elon Musk teases TSMC as potential Terafab partner
