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’s xAI closes upsized $20B Series E funding round
xAI announced the investment round in a post on its official website.
xAI has closed an upsized $20 billion Series E funding round, exceeding the initial $15 billion target to fuel rapid infrastructure scaling and AI product development.
xAI announced the investment round in a post on its official website.
A $20 billion Series E round
As noted by the artificial intelligence startup in its post, the Series E funding round attracted a diverse group of investors, including Valor Equity Partners, Stepstone Group, Fidelity Management & Research Company, Qatar Investment Authority, MGX, and Baron Capital Group, among others.
Strategic partners NVIDIA and Cisco Investments also continued support for building the world’s largest GPU clusters.
As xAI stated, “This financing will accelerate our world-leading infrastructure buildout, enable the rapid development and deployment of transformative AI products reaching billions of users, and fuel groundbreaking research advancing xAI’s core mission: Understanding the Universe.”
xAI’s core mission
Th Series E funding builds on xAI’s previous rounds, powering Grok advancements and massive compute expansions like the Memphis supercluster. The upsized demand reflects growing recognition of xAI’s potential in frontier AI.
xAI also highlighted several of its breakthroughs in 2025, from the buildout of Colossus I and II, which ended with over 1 million H100 GPU equivalents, and the rollout of the Grok 4 Series, Grok Voice, and Grok Imagine, among others. The company also confirmed that work is already underway to train the flagship large language model’s next iteration, Grok 5.
“Looking ahead, Grok 5 is currently in training, and we are focused on launching innovative new consumer and enterprise products that harness the power of Grok, Colossus, and 𝕏 to transform how we live, work, and play,” xAI wrote.
Tesla (NASDAQ: TSLA) stock received a price target update from Pierre Ferragu of Wall Street firm New Street Research, citing the company’s growing lead in self-driving and autonomy.
On Tuesday, Ferragu bumped his price target from $520 to $600, stating that the consensus from the Consumer Electronics Show in Las Vegas was that Tesla’s lead in autonomy has been sustained, is growing, and sits at a multiple-year lead over its competitors.
CES 2026 validates Tesla’s FSD strategy, but there’s a big lag for rivals: analyst
“The signal from Vegas is loud and clear,” the analyst writes. “The industry isn’t catching up to Tesla; it is actively validating Tesla’s strategy…just with a 12-year lag.”
The note shows that the company’s prowess in vehicle autonomy is being solidified by lagging competitors that claim to have the best method. The only problem is that Tesla’s Vision-based approach, which it adopted back in 2022 with the Model 3 and Model Y initially, has been proven to be more effective than competitors’ approach, which utilizes other technology, such as LiDAR and sensors.
Currently, Tesla shares are sitting at around $433, as the company’s stock price closed at $432.96 on Tuesday afternoon.
Ferragu’s consensus on Tesla shares echoes that of other Wall Street analysts who are bullish on the company’s stock and position within the AI, autonomy, and robotics sector.
Dan Ives of Wedbush wrote in a note in mid-December that he anticipates Tesla having a massive 2026, and could reach a $3 trillion valuation this year, especially with the “AI chapter” taking hold of the narrative at the company.
Ives also said that the big step in the right direction for Tesla will be initiating production of the Cybercab, as well as expanding on the Robotaxi program through the next 12 months:
“…as full-scale volume production begins with the autonomous and robotics roadmap…The company has started to test the all-important Cybercab in Austin over the past few weeks, which is an incremental step towards launching in 2026 with important volume production of Cybercabs starting in April/May, which remains the golden goose in unlocking TSLA’s AI valuation.”
Tesla analyst breaks down delivery report: ‘A step in the right direction’
Tesla has transitioned from an automaker to a full-fledged AI company, and its Robotaxi and Cybercab programs, fueled by the Full Self-Driving suite, are leading the charge moving forward. In 2026, there are major goals the company has outlined. The first is removing Safety Drivers from vehicles in Austin, Texas, one of the areas where it operates a ride-hailing service within the U.S.
Ultimately, Tesla will aim to launch a Level 5 autonomy suite to the public in the coming years.
Elon Musk
Elon Musk’s Biggest Revelations on AI, Robots, and the Future of Work from the Moonshots Podcast
Elon Musk’s appearance on the Moonshots with Peter Diamandis podcast was packed with bold predictions, candid admissions, and surprising tech insights. The nearly three-hour conversation covered everything from artificial intelligence to humanoid robots, geopolitics, and the future of work. Here are the top 10 most intriguing takeaways:
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Aggressive AGI Timeline Predictions
Musk offered a detailed view on when artificial general intelligence (AGI) could emerge, suggesting it may arrive sooner than many expect, emphasizing both transformative potential and risks.
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U.S. vs. China in the AI Race
He discussed the strategic competition between the United States and China over AI development, noting that geopolitical dynamics will shape how and who leads in the next decades.
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Future of Job Markets
Musk touched on how AI and automation could reshape employment, predicting massive boosts in productivity alongside potential disruptions in traditional work structures.
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Clean Energy Transition
A recurring theme was the role of clean energy in future economies, with Musk reiterating the importance of scaling sustainable power generation and storage.
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Humanoid Robots Are Coming
On the podcast, Musk elaborated on Tesla’s work on humanoid robots, hinting at timelines and applications that go beyond factories to general-purpose assistance.
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Tesla Roadster “Last Human-Driven Car”
Outside the core discussion topics, Musk teased features of the upcoming Tesla Roadster — calling it “the best of the last of the human-driven cars” and suggesting safety won’t be its main selling point.
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The Role of AI in Clean Energy and Robotics
Linking AI to both energy optimization and robotics, Musk explained how smarter systems could accelerate decarbonization and task automation across industries.
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U.S. Innovation Leadership
Musk argued that maintaining American leadership in key tech sectors like AI, space, and robotics should be a national priority, with thoughtful policy and investment.
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Job Creation vs. Job Elimination
While acknowledging automation’s disruptive effects, he also outlined scenarios where new industries and opportunities could emerge, particularly in AI, space, and advanced manufacturing.
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Long-Term Vision for Humanity
Throughout the conversation, Musk revisited his long-term philosophical views — including a belief in humanity’s responsibility to become a multi-planetary and technologically empowered species.
Whether you agree with Musk’s optimism or not, the podcast offers a window into the thinking of one of the most influential figures in tech today, in and why his visions continue to spark debate and inspiration.
Elon Musk’s xAI closes upsized $20B Series E funding round
Tesla gets price target bump, citing growing lead in self-driving
