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.”
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 has rolled out a new Supercharging safety feature in the United States, one that will answer concerns that some owners may have if they need to leave in a pinch.
It is also a suitable alternative for non-Tesla chargers, like third-party options that feature J1772 or CCS to NACS adapters.
The feature has been available in Europe for some time, but it is now rolling out to Model 3 and Model Y owners in the U.S.
With Software Update 2026.2.3, Tesla is launching the Unlatching Charge Cable function, which will now utilize the left rear door handle to release the charging cable from the port. The release notes state:
“Charging can now be stopped and the charge cable released by pulling and holding the rear left door handle for three seconds, provided the vehicle is unlocked, and a recognized key is nearby. This is especially useful when the charge cable doesn’t have an unlatch button. You can still release the cable using the vehicle touchscreen or the Tesla app.”
The feature was first spotted by Not a Tesla App.
This is an especially nice feature for those who commonly charge at third-party locations that utilize plugs that are not NACS, which is the Tesla standard.
For example, after plugging into a J1772 charger, you will still be required to unlock the port through the touchscreen, which is a minor inconvenience, but an inconvenience nonetheless.
Additionally, it could be viewed as a safety feature, especially if you’re in need of unlocking the charger from your car in a pinch. Simply holding open the handle on the rear driver’s door will now unhatch the port from the car, allowing you to pull it out and place it back in its housing.
This feature is currently only available on the Model 3 and Model Y, so Model S, Model X, and Cybertruck owners will have to wait for a different solution to this particular feature.
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LG Energy Solution pursuing battery deal for Tesla Optimus, other humanoid robots: report
Optimus is expected to be one of Tesla’s most ambitious projects, with Elon Musk estimating that the humanoid robot could be the company’s most important product.
A recent report has suggested that LG Energy Solution is in discussions to supply batteries for Tesla’s Optimus humanoid robot.
Optimus is expected to be one of Tesla’s most ambitious projects, with Elon Musk estimating that the humanoid robot could be the company’s most important product.
Humanoid robot battery deals
LG Energy Solution shares jumped more than 11% on the 28th after a report from the Korea Economic Daily claimed that the company is pursuing battery supply and joint development agreements with several humanoid robot makers. These reportedly include Tesla, which is developing Optimus, as well as multiple Chinese robotics companies.
China is already home to several leading battery manufacturers, such as CATL and BYD, making the robot makers’ reported interest in LG Energy Solution quite interesting. Market participants interpreted the reported outreach as a signal that performance requirements for humanoid robots may favor battery chemistries developed by companies like LG.
LF Energy Solution vs rivals
According to the report, energy density is believed to be the primary reason humanoid robot developers are evaluating LG Energy Solution’s batteries. Unlike electric vehicles, humanoid robots have significantly less space available for battery packs while requiring substantial power to operate dozens of joint motors and onboard artificial intelligence processors.
LG Energy Solution’s ternary lithium batteries offer higher energy density compared with rivals’ lithium iron phosphate (LFP) batteries, which are widely used by Chinese EV manufacturers. That advantage could prove critical for humanoid robots, where runtime, weight, and compact packaging are key design constraints.
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Tesla receives approval for FSD Supervised tests in Sweden
Tesla confirmed that it has been granted permission to test FSD Supervised vehicles across Sweden in a press release.
Tesla has received regulatory approval to begin tests of its Full Self-Driving Supervised system on public roads in Sweden, a notable step in the company’s efforts to secure FSD approval for the wider European market.
FSD Supervised testing in Sweden
Tesla confirmed that it has been granted permission to test FSD Supervised vehicles across Sweden following cooperation with national authorities and local municipalities. The approval covers the Swedish Transport Administration’s entire road network, as well as urban and highways in the Municipality of Nacka.
Tesla shared some insights into its recent FSD approvals in a press release. “The approval shows that cooperation between authorities, municipalities and businesses enables technological leaps and Nacka Municipality is the first to become part of the transport system of the future. The fact that the driving of the future is also being tested on Swedish roads is an important step in the development towards autonomy in real everyday traffic,” the company noted.
With approval secured for FSD tests, Tesla can now evaluate the system’s performance in diverse environments, including dense urban areas and high-speed roadways across Sweden, as noted in a report from Allt Om Elbil. Tesla highlighted that the continued development of advanced driver assistance systems is expected to pave the way for improved traffic safety, increased accessibility, and lower emissions, particularly in populated city centers.
Tesla FSD Supervised Europe rollout
FSD Supervised is already available to drivers in several global markets, including Australia, Canada, China, Mexico, New Zealand, and the United States. The system is capable of handling city and highway driving tasks such as steering, acceleration, braking, and lane changes, though it still requires drivers to supervise the vehicle’s operations.
Tesla has stated that FSD Supervised has accumulated extensive driving data from its existing markets. In Europe, however, deployment remains subject to regulatory approval, with Tesla currently awaiting clearance from relevant authorities.
The company reiterated that it expects to start rolling out FSD Supervised to European customers in early 2026, pending approvals. It would then be unsurprising if the company secures approvals for FSD tests in other European territories in the coming months.
Tesla rolls out new Supercharging safety feature in the U.S.
LG Energy Solution pursuing battery deal for Tesla Optimus, other humanoid robots: report
