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
A close-up image of a Cybercab engineering vehicle in Peabody, Massachusetts, reveals a compact triangular side repeater camera housing equipped with an integrated washer mechanism.
This seemingly small hardware addition could prove to be one of the most critical components for achieving reliable, unsupervised Full Self-Driving (FSD) — not just for the dedicated Robotaxi but potentially for existing AI4-equipped vehicles as well.
The washer system’s importance cannot be overstated in Tesla’s vision-only autonomy approach. Cameras are the sole sensory input for the neural networks powering FSD, constantly interpreting the environment for safe navigation. In real-world conditions, however, lenses quickly accumulate rain, snow, mud, dust, or road spray.
Many of us Tesla owners, especially those who deal with any sort of winter weather at all, know the all-too-common alert that pops up when cameras are obstructed:
Even brief obstructions can drop perception confidence, trigger safety disengagements, or force the vehicle to pull over, although these are relatively rare. Instead, most of the time, the camera will need a wipe from the owner next time they stop the car.
But unlike human drivers who can manually clear their view, a Robotaxi operating 24/7 without a steering wheel or mirrors must maintain pristine vision autonomously. The Cybercab’s side repeater washer delivers targeted cleaning bursts precisely where needed for merging, lane changes, and blind-spot monitoring — functions that demand uninterrupted visibility from the external cameras:
And this is how the side camera and washer look like on a Cybercab. This is from an Engineering vehicle in Peabody MA. pic.twitter.com/Re8VknpmLM
— Tobias Goebel (Unsupervised) (@tpgoebel) June 17, 2026
This hardware directly tackles a known pain point in current FSD deployments. Owners frequently report camera-related alerts during inclement weather, which is understandable, but needs to be solved for a true autonomous experience.
For a production Robotaxi fleet aiming for high utilization and minimal downtime, robust washer systems represent a foundational reliability upgrade; essentially, they’re a must-have. Early sightings suggest the design may extend to rear cameras as well, creating a comprehensive cleaning architecture that keeps the entire vision suite operational in harsh environments.
Without it, even the most advanced neural nets struggle when their “eyes” are compromised.
What Does This Mean for AI4 Cars?
This Cybercab detail raises timely questions for AI4 cars already on the road. While Hardware 4 delivers superior compute and camera resolution compared to earlier versions, production models typically lack dedicated side and rear washers. Tesla has included them on Model Y robotaxis that it is using in the fleet:
Tesla Robotaxi has a highly-requested hardware feature not available on typical Model Ys
As Tesla refines unsupervised FSD for broader release, the gap in environmental resilience becomes evident. Software improvements can help mitigate issues, but they cannot fully replace physical cleaning in heavy rain or muddy conditions. Analysts and owners increasingly speculate that AI4 vehicles may eventually require similar washer retrofits — or a future AI4.5 variant — to match the Cybercab’s all-weather readiness and support the same level of autonomy.
As testing progresses, the Cybercab’s washer mechanism highlights Tesla’s pragmatic focus on real-world robustness. It may well become the hardware piece that determines how quickly and reliably FSD scales from prototypes to everyday vehicles.
Elon Musk
Elon Musk just upped his Tesla stake further fueling SpaceX merger conversation
Elon Musk just collected a $116 billion Tesla payday and the timing is eye-opening
Elon Musk quietly collected one of the largest single-transaction paydays in corporate history on Monday. A Form 4 filed with the SEC on June 17, 2026 disclosed that Musk exercised 303,960,630 Tesla stock options from his 2018 compensation package, with the transaction dated June 16. No shares were sold on the open market.
The numbers are straightforward but striking. Musk exercised the options at a split-adjusted strike price of $23.34, with Tesla closing at $404.66 that day, putting the spread at $381.32 per share and generating roughly $115.9 billion in paper gains in a single transaction. To cover the exercise cost, Tesla withheld 17,531,857 shares through a net share settlement, meaning Musk paid nothing out of pocket.
For perspective, in 2018, Elon Musk’s award was originally approved by Tesla shareholders on March 21, 2018, and structured entirely around performance milestones that many analysts at the time called unreachable. Every tranche eventually vested. The original grant covered 20,264,042 shares at $350.02, which after Tesla’s 5-for-1 split in 2020 and 3-for-1 split in 2022 adjusted to 303,960,630 shares at $23.34. A Delaware court rescinded the award in January 2024, ruling the board was conflicted. As Teslarati reported, Tesla shareholders voted to ratify the package anyway in June 2024 by a wide margin. The Delaware Supreme Court reversed the decision in December 2025, finding full cancellation too extreme, and Tesla’s board signed an Implementation Agreement on April 21, 2026 to formally deliver the shares.
The Tesla and SpaceX merger everyone is talking about is quietly building
The timing and structure of the Form 4 filing carries more weight than a routine stock option exercise typically would. Musk exercised his 2018 Tesla award on June 16, a week into SpaceX completing its IPO and trading publicly, and giving SpaceX a public market valuation and share currency for the first time in the company’s history. A stock-for-stock merger between two companies requires the acquiring entity to have tradeable shares it can offer to the target’s shareholders, and SpaceX now has exactly that. At the same time, Musk just increased his direct Tesla voting power to approximately 20%, giving him greater influence over any shareholder vote that a merger would require. The restricted shares he received cannot be sold until 2033, which removes any near-term incentive to cash out and instead positions this stake as long-term structural collateral in a deal. Additionally, Musk’s two companies are already deeply intertwined through shared semiconductor fabrication at their joint TERAFAB facility in Austin, cross-company supply chain transactions, and Tesla’s $2 billion investment in xAI prior to the SpaceX-xAI merger.
Wedbush analyst Dan Ives has publicly placed the odds of a Tesla and SpaceX combination at 80% to 90% by early 2027. The Implementation Agreement that made Monday’s exercise possible was signed on April 21, 2026, roughly two months before the SpaceX IPO closed. That sequencing, building Musk’s Tesla ownership to its highest point ever immediately before SpaceX gains the public currency needed to acquire it, is either an extraordinary coincidence or a carefully staged foundation for the largest corporate merger in history.
Tesla Full Self-Driving is going to be getting a major parking upgrade. That’s according to CEO Elon Musk, who detailed a crafty new feature that will improve parking preferences, removing a layer of human input.
Musk said that upcoming releases of Full Self-Driving will “remember your parking preferences.” It will go to the location you prefer, based on where you’ve parked in the past, instead of taking the first spot available, which is where the suite is currently.
The CEO went on to explain that destination parking is “by far” the biggest reason for intervention during FSD operation. We’d have to believe this is true; many takeovers in my Model Y, which runs the latest version of FSD as it is in the Early Access Program, are due to parking because it chooses a spot I do not want to be in.
Many times, as soon as I enter a parking lot, I take over and park manually. I prefer to park away from the entrance of wherever I am, away from cars. Too many lessons learned over the years from people with free-swinging doors.
Upcoming releases of FSD will remember your parking preferences, so that the car goes to the right location at your home, office, school drop off, etc.
Destination parking is by far the biggest reason people now intervene with FSD. Critical safety interventions are extremely…
— Elon Musk (@elonmusk) June 17, 2026
We’d imagine these new updates will also solve things like parking orientation. Let’s say when you arrive at work, you always park in the third spot in the third row, and you prefer to back in. It seems as if Musk is implying that your car will now do this, learning from takeovers and aiming to eliminate the need to manually park whenever possible.
This is a major upgrade because parking is a major shortcoming of FSD currently. We’ve requested things like manual input of parking preferences, choosing to park far away, first available, or away from cars, for example.
This is a big reason Parking Preferences with Supervised FSD will be so valuable.
If possible, parking a little further away and being distant from people like this is worth it. https://t.co/1YqQLgnfTz pic.twitter.com/3Ac71KQiQ3
— TESLARATI (@Teslarati) June 7, 2026
However, some have used the option of dropping a pin at the location you’d like to park at your destination. This has worked some of the time, but FSD will still choose to park in whatever it sees first.
Musk did not give a timetable for when the improvements would be released, but it is likely to come soon. Tesla has been releasing a new FSD version every few weeks, so we may not have to wait long to test it.
Tesla Cybercab has one important piece that AI4 cars might need for FSD
Elon Musk just upped his Tesla stake further fueling SpaceX merger conversation
