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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.

Tesla details its self-driving Supercomputer that will bring in the Dojo era

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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:

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Tesla Patent Parallel Processing System Runtime State Reload by Joey Klender on Scribd

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 adds new feature that will be great for crowded parking situations

This is the most recent iteration of the app and was priming owners for the slowly-released Holiday Update.

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Credit: Grok

Tesla has added a new feature that will be great for crowded parking lots, congested parking garages, or other confusing times when you cannot seem to pinpoint where your car went.

Tesla has added a new Vehicle Locator feature to the Tesla App with App Update v4.51.5.

This is the most recent iteration of the app and was priming owners for the slowly-released Holiday Update.

While there are several new features, which we will reveal later in this article, perhaps one of the coolest is that of the Vehicle Locator, which will now point you in the direction of your car using a directional arrow on the home screen. This is similar to what Apple uses to find devices:

In real time, the arrow gives an accurate depiction of which direction you should walk in to find your car. This seems extremely helpful in large parking lots or unfamiliar shopping centers.

Getting to your car after a sporting event is an event all in itself; this feature will undoubtedly help with it:

Tesla’s previous app versions revealed the address at which you could locate your car, which was great if you parked on the street in a city setting. It was also possible to use the map within the app to locate your car.

However, this new feature gives a more definitive location for your car and helps with the navigation to it, instead of potentially walking randomly.

It also reveals the distance you are from your car, which is a big plus.

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Along with this new addition, Tesla added Photobooth features, Dog Mode Live Activity, Custom Wraps and Tints for Colorizer, and Dashcam Clip details.

All in all, this App update was pretty robust.

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Tesla CEO Elon Musk shades Waymo: ‘Never really had a chance’

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Credit: Tesla

Tesla CEO Elon Musk shaded Waymo in a post on X on Wednesday, stating the company “never really had a chance” and that it “will be obvious in hindsight.”

Tesla and Waymo are the two primary contributors to the self-driving efforts in the United States, with both operating driverless ride-hailing services in the country. Tesla does have a Safety Monitor present in its vehicles in Austin, Texas, and someone in the driver’s seat in its Bay Area operation.

Musk says the Austin operation will be completely void of any Safety Monitors by the end of the year.

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With the two companies being the main members of the driverless movement in the U.S., there is certainly a rivalry. The two have sparred back and forth with their geofences, or service areas, in both Austin and the Bay Area.

While that is a metric for comparison now, ultimately, it will not matter in the coming years, as the two companies will likely operate in a similar fashion.

Waymo has geared its business toward larger cities, and Tesla has said that its self-driving efforts will expand to every single one of its vehicles in any location globally. This is where the true difference between the two lies, along with the fact that Tesla uses its own vehicles, while Waymo has several models in its lineup from different manufacturers.

The two also have different ideas on how to solve self-driving, as Tesla uses a vision-only approach. Waymo relies on several things, including LiDAR, which Musk once called “a fool’s errand.”

This is where Tesla sets itself apart from the competition, and Musk highlighted the company’s position against Waymo.

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Jeff Dean, the Chief Scientist for Google DeepMind, said on X:

“I don’t think Tesla has anywhere near the volume of rider-only autonomous miles that Waymo has (96M for Waymo, as of today). The safety data is quite compelling for Waymo, as well.”

Musk replied:

“Waymo never really had a chance against Tesla. This will be obvious in hindsight.”

Tesla stands to have a much larger fleet of vehicles in the coming years if it chooses to activate Robotaxi services with all passenger vehicles. A simple Over-the-Air update will activate this capability, while Waymo would likely be confined to the vehicles it commissions as Robotaxis.

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Tesla supplier Samsung preps for AI5 production with latest move

According to a new report from Sedaily, Samsung is accelerating its preparation for U.S. production of the AI5 chips by hiring veteran engineers for its Customer Engineering team.

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Credit: Tesla

Tesla supplier Samsung is preparing to manufacture the AI5 chip, which will launch the company’s self-driving efforts even further, with its latest move.

According to a new report from Sedaily, Samsung is accelerating its preparation for U.S. production of the AI5 chips by hiring veteran engineers for its Customer Engineering team, which will help resolve complex foundry challenges, stabilize production and yields, and ensure manufacturing goes smoothly for the new project.

The hiring push signals that Tesla’s AI5 project is moving forward quickly at Samsung, which was one of two suppliers to win a contract order from the world’s leading EV maker.

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TSMC is the other. TSMC is using its 3nm process, reportedly, while Samsung will do a 2nm as a litmus test for the process.

The different versions are due to the fact that “they translate designs to physical form differently,” CEO Elon Musk said recently. The goal is for the two to operate identically, obviously, which is a challenge.

Some might remember Apple’s A9 “Chipgate” saga, which found that the chips differed in performance because of different manufacturers.

The AI5 chip is Tesla’s next-generation hardware chip for its self-driving program, but it will also contribute to the Optimus program and other AI-driven features in both vehicles and other projects. Currently, Tesla utilizes AI4, formerly known as HW4 or Hardware 4, in its vehicles.

Tesla teases new AI5 chip that will revolutionize self-driving

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AI5 is specialized for use by Tesla as it will work in conjunction with the company’s Neural Networks, focusing on real-time inference to make safe and logical decisions during operation.

Musk said it was an “amazing design” and an “immense jump” from Tesla’s current AI4 chip. It will be roughly 40 times faster, and have 8 times the raw compute, with 9 times the memory capacity. It is also expected to be three times as efficient per watt as AI4.

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AI5 will make its way into “maybe a small number of units” next year, Musk confirmed. However, it will not make its way to high-volume production until 2027. AI5 is not the last step, either, as Musk has already confirmed AI6 would likely enter production in mid-2028.

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