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
Elon Musk
Elon Musk handed Grok something no other AI company can get their hands on
Elon Musk says SpaceX will feed engineering data into Grok’s next model, avoiding restricted material.
Elon Musk said Tuesday that SpaceX will feed its internal engineering data into the next major training run for Grok, the AI model now folded into SpaceX following February’s merger. In a post on X, Musk wrote that SpaceX’s “massive corpus of world-class engineering data,” excluding anything restricted under U.S. arms export law, will be added during supplemental training of what he called the “2T run,” a reference to a roughly two trillion parameter model that would nearly double the parameters behind the latest Grok 4.5 that’s rolling out.
SpaceX’s massive corpus of world-class engineering data (excluding material blocked by ITAR) will be added during supplemental training of the 2T run.
This will dramatically improve Grok’s engineering capabilities. https://t.co/BbQEViFByn
— Elon Musk (@elonmusk) July 21, 2026
The excluded material that Musk is referring to would fall under the International Traffic in Arms Regulations (ITAR), which restricts export of technical data tied to defense and space hardware. That likely rules out propulsion specifics for Merlin and Raptor engines along with guidance and control details for SpaceX’s launch vehicles, but leaves manufacturing knowledge, materials science, and Starlink hardware design on the table.
The announcement extends a pattern that has been building since SpaceX’s Nasdaq debut in June, when the company went public with Grok and xAI’s Colossus supercomputer folded into the pitch to investors.
Days after that listing, SpaceX closed its $60 billion all stock acquisition of coding startup Cursor, giving xAI both enterprise software distribution and a stream of real world developer data to train on. Grok 4.5 launched July 8 running partly on that Cursor training data, with Musk describing it as roughly comparable to Anthropic’s Opus 4.7 but faster and cheaper to run.
Feeding SpaceX’s own engineering data into the next AI model follows the same logic Musk has applied across xAI’s sister companies. Tesla supplies real world driving data and manufacturing expertise, X supplies conversational data, and now SpaceX supplies aerospace engineering data built up since 2002.
Musk did not give a release date for the upcoming AI model, referred to elsewhere as Grok 4.6. He has said the two trillion parameter run is in its final training phase and expected to wrap this week.
Tesla has extended its Bay Area ride-hailing service to include pickups and drop-offs at San Francisco International Airport (SFO). The update, shared via the company’s official channels on July 21, allows users in the region to request rides directly to and from one of California’s busiest airports.
The expansion builds on Tesla’s secured limousine permit for SFO operations. Public records show the permit became effective March 20, 2026, and remains active through January 31, 2027. Tesla vehicles operating the service now display authorized limousine permits issued by the City and County of San Francisco.
Our Bay Area rideshare service now goes to SFO ✈️
— Tesla AI (@Tesla_AI) July 21, 2026
Tesla’s ride-hailing program in California relies on Model Y vehicles equipped with Full Self-Driving (Supervised) technology. Human safety drivers remain present in compliance with state regulations, distinguishing the service from fully driverless operations.
The Bay Area geofence covers a broad area spanning north of San Francisco to south of San Jose, offering extensive connectivity across the region.
UPDATE: Elon Musk reveals why Tesla didn’t say ‘Robotaxi’ upon California launch
This SFO addition follows earlier progress at other Bay Area airports. Tesla previously expanded service to San Jose Mineta International Airport (SJC) in late 2025. The company had engaged with SFO, SJC, and Oakland International Airport officials as early as September 2025 to secure necessary approvals for passenger transport.
The service provides a new option for travelers seeking electric, app-based transportation integrated with Tesla’s ecosystem. Rides are booked through Tesla’s dedicated ride-hailing application, which handles matching, routing, and payments. Pricing follows standard ride-hailing models, with potential adjustments based on distance, time, and demand.
Tesla’s California ride-hailing program launched in July 2025 with an initial invite-only rollout in the Bay Area. It started alongside operations in Austin, Texas, marking the company’s second major U.S. market.
The Bay Area remains a primary focus in California, with service centered on high-demand corridors connecting residential, commercial, and now major transportation hubs. This latest airport integration represents a practical step in Tesla’s broader mobility ambitions within the state.
Tesla has officially revealed its 2026 Summer Update, which comes with a variety of crazy new features, including Navigation fixes that owners have been wanting for months.
Tesla routinely releases a larger update with the Spring, Summer, Fall, and Winter updates, where it ships a variety of new features, bug fixes, and other additions to customer cars.
The 2026 Spring Update featured things like “Hey Grok” voice assistance, a redesigned self-driving app, Unreal Engine visual upgrades, and more.
🚨 TESLA’S SUMMER UPDATE FOR 2026 IS HERE:
Featuring:
✅ Self-Driving Stats in Mobile App
✅ Caraoke with Scoring
✅ Automatic Navigation
✅ Preferred Routes
✅ Set Arrival Energy from Mobile App
✅ Send Custom Wraps from Mobile App
✅ Rear Display Lock
✅ Other Improvements
🔌… https://t.co/C9IW3egEhH— TESLARATI (@Teslarati) July 21, 2026
Tesla’s Summer Release has about ten new features; we’ll show you each and detail them below:
New Grok Voice Commands
“Grok can now make phone calls, search and play music, adjust climate, open the glovebox, and answer questions about your Tesla.”
Self-Driving Stats in Mobile App
“View and share self-driving stats from the mobile app.”
Caraoke With Scoring
“Caraoke now scores your singing while in Park. High scores are saved to your Tesla profile.”
Automatic Navigation
“Automatic Navigation now adapts to your routine.
In addition to Home, Work, and upcoming calendar events, your vehicle can now suggest and route to places you visit regularly – like a school drop-off on the way to work, or the gym on the way home.”
Preferred Routes
“For a more personalized experience, navigation now prioritizes routes that you’ve taken before”
Set Arrival Energy from Mobile App
“Set your desired Arrival Energy from your phone.”
Send Custom Wraps from Mobile App
“Skip the USB drive and upload a custom wrap of your car from the mobile app. Instructions for creating a custom wrap here: https://github.com/teslamotors/custom-wraps.”
Rear Display Lock
“Kids can watch content on the rear screen, but only the front row can control it through the rear screen app.”
Other Improvements
- Find Superchargers by name when searching for a destination
- Add Apple Music songs to queue from search and artist page
- Set your preferred zoom level for the Self-Driving visualization
- Intro animations for new Model 3 and Y
Elon Musk handed Grok something no other AI company can get their hands on
Tesla expands ridesharing service in California to new hotspot
