A recently published Tesla patent application titled “System and Method for Handling Errors in a Vehicle Neural Network Processor” describes a way to safely handle errors encountered in self-driving software. Rather than risking delays in driving responses that result from input data errors, a signal is sent to ignore the bad information and continue processing as usual. Tesla’s application was published May 23, 2019 as International Publication No. WO/2019/099941.
During self-driving operations in Tesla’s program, streams of real-time input data are received and used to both train its neural network and initiate a vehicle response to what’s being processed. If something in the data is erroneous or causes a delay in processing, the real-world impact can be disastrous if not handled properly. For example, in a fast-moving vehicle, sensor data can become stale very quickly and cause the self-driving software to respond to an environment that no longer exists. This can result in accidents, property damage, injury, and/or death. The solution presented in Tesla’s patent application attempts to avoid such processing delays altogether and thus improves the safety of the self-driving software overall.
Tesla’s patent application describes the issue as follows:
“Some types of errors may cause neural network processor to hang or time out. That is, one or more portions of neural network processor may freeze or otherwise remain inactive for more than a predetermined amount of time. When a timeout error is encountered, [the] neural network processor may cease to provide output data and/or respond to input data. Other types of errors, such as program errors and/or data errors, may cause the output data generated by [the] neural network processor to be corrupted. When such errors are encountered, [the] neural network processor may continue to provide output data, but the result may be incorrect, meaningless, and/or otherwise unusable.”
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- Tesla’s self-driving patent application focuses on handling errors found in its neural network. | Image: Tesla/WIPO
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- Tesla’s self-driving patent application focuses on handling errors found in its neural network. | Image: Tesla/WIPO
On its face, the concept behind invention may seem somewhat simple, but likely due to the complexity of neural networks and the field of autonomous driving still being fairly new, Tesla’s solution is unique and innovative. At the international review stage in the patent application process, the Examiner found that Tesla’s patent was novel (new) compared to similar neural network inventions already in the field. Specifically, the following was commented in a Written Opinion:
“Although neural network processors are well known in the art, including in the operation of a vehicle, the addition of having the controller signal that a pending data result is tainted, or incorrect, without terminating the execution of the network, improves upon prior art processors by ensuring the computations of the processor in the vehicle continue while ignoring data determined to be in error, and would require a complexity beyond the ordinary skill, and therefore…meets the…criteria for patentability.”
Concerns about Tesla’s Autopilot software were recently hit by a report published by Consumer Reports wherein the consumer advocacy group concluded that Navigate on Autopilot with autonomic lane changes was more of a liability than an asset. The report stated that, since the feature requires drivers to be one step ahead of the system while it is engaged, it still needs improvement, although the same group found Tesla’s autonomous driving software to be more capable than the competition. However, the report was only focused on how Navigate on Autopilot operates when changing lanes confirmation and warnings are disabled, contrary to scathing headlines which lumped all of Autopilot’s features together with the review.
This most recent patent application shows that Tesla is continuously improving its self-driving features, if that wasn’t already obvious from the company’s frequent over-the-air software releases.
At Tesla’s Autonomy Day for investors last month, CEO Elon Musk declared that the company’s Full Self-Driving computer was objectively the “best in the world”. As more information becomes available, such as presentations on Tesla’s technology and in patent applications, Musk’s confidence expressed in his statement becomes more clear. Full Self-Driving is expected to be feature-complete this year and will become publicly available as regulatory hurdles are overcome.
Elon Musk
Elon Musk’s xAI brings 1GW Colossus 2 AI training cluster online
Elon Musk shared his update in a recent post on social media platform X.
xAI has brought its Colossus 2 supercomputer online, making it the first gigawatt-scale AI training cluster in the world, and it’s about to get even bigger in a few months.
Elon Musk shared his update in a recent post on social media platform X.
Colossus 2 goes live
The Colossus 2 supercomputer, together with its predecessor, Colossus 1, are used by xAI to primarily train and refine the company’s Grok large language model. In a post on X, Musk stated that Colossus 2 is already operational, making it the first gigawatt training cluster in the world.
But what’s even more remarkable is that it would be upgraded to 1.5 GW of power in April. Even in its current iteration, however, the Colossus 2 supercomputer already exceeds the peak demand of San Francisco.
Commentary from users of the social media platform highlighted the speed of execution behind the project. Colossus 1 went from site preparation to full operation in 122 days, while Colossus 2 went live by crossing the 1-GW barrier and is targeting a total capacity of roughly 2 GW. This far exceeds the speed of xAI’s primary rivals.
Funding fuels rapid expansion
xAI’s Colossus 2 launch follows xAI’s recently closed, upsized $20 billion Series E funding round, which exceeded its initial $15 billion target. The company said the capital will be used to accelerate infrastructure scaling and AI product development.
The round attracted a broad group of investors, including Valor Equity Partners, Stepstone Group, Fidelity Management & Research Company, Qatar Investment Authority, MGX, and Baron Capital Group. Strategic partners NVIDIA and Cisco also continued their support, helping xAI build what it describes as the world’s largest GPU clusters.
xAI said the funding will accelerate its infrastructure buildout, enable rapid deployment of AI products to billions of users, and support research tied to its mission of understanding the universe. The company noted that its Colossus 1 and 2 systems now represent more than one million H100 GPU equivalents, alongside recent releases including the Grok 4 series, Grok Voice, and Grok Imagine. Training is also already underway for its next flagship model, Grok 5.
Elon Musk
Tesla AI5 chip nears completion, Elon Musk teases 9-month development cadence
The Tesla CEO shared his recent insights in a post on social media platform X.
Tesla’s next-generation AI5 chip is nearly complete, and work on its successor is already underway, as per a recent update from Elon Musk.
The Tesla CEO shared his recent insights in a post on social media platform X.
Musk details AI chip roadmap
In his post, Elon Musk stated that Tesla’s AI5 chip design is “almost done,” while AI6 has already entered early development. Musk added that Tesla plans to continue iterating rapidly, with AI7, AI8, AI9, and future generations targeting a nine-month design cycle.
He also noted that Tesla’s in-house chips could become the highest-volume AI processors in the world. Musk framed his update as a recruiting message, encouraging engineers to join Tesla’s AI and chip development teams.
Tesla community member Herbert Ong highlighted the strategic importance of the timeline, noting that faster chip cycles enable quicker learning, faster iteration, and a compounding advantage in AI and autonomy that becomes increasingly difficult for competitors to close.
AI5 manufacturing takes shape
Musk’s comments align with earlier reporting on AI5’s production plans. In December, it was reported that Samsung is preparing to manufacture Tesla’s AI5 chip, accelerating hiring for experienced engineers to support U.S. production and address complex foundry challenges.
Samsung is one of two suppliers selected for AI5, alongside TSMC. The companies are expected to produce different versions of the AI5 chip, with TSMC reportedly using a 3nm process and Samsung using a 2nm process.
Musk has previously stated that while different foundries translate chip designs into physical silicon in different ways, the goal is for both versions of the Tesla AI5 chip to operate identically. AI5 will succeed Tesla’s current AI4 hardware, formerly known as Hardware 4, and is expected to support the company’s Full Self-Driving system as well as other AI-driven efforts, including Optimus.
News
Tesla Model Y and Model 3 named safest vehicles tested by ANCAP in 2025
According to ANCAP in a press release, the Tesla Model Y achieved the highest overall weighted score of any vehicle assessed in 2025.
The Tesla Model Y recorded the highest overall safety score of any vehicle tested by ANCAP in 2025. The Tesla Model 3 also delivered strong results, reinforcing the automaker’s safety leadership in Australia and New Zealand.
According to ANCAP in a press release, the Tesla Model Y achieved the highest overall weighted score of any vehicle assessed in 2025. ANCAP’s 2025 tests evaluated vehicles across four key pillars: Adult Occupant Protection, Child Occupant Protection, Vulnerable Road User Protection, and Safety Assist technologies.
The Model Y posted consistently strong results in all four categories, distinguishing itself through a system-based safety approach that combines structural crash protection with advanced driver-assistance features such as autonomous emergency braking, lane support, and driver monitoring.
This marked the second time the Model Y has topped ANCAP’s annual safety rankings. The Model Y’s previous version was also ANCAP’s top performer in 2022.
The Tesla Model 3 also delivered a strong performance in ANCAP’s 2025 tests, contributing to Tesla’s broader safety presence across segments. Similar to the Model Y, the Model 3 also earned impressive scores across the ANCAP’s four pillars. This made the vehicle the top performer in the Medium Car category.
ANCAP Chief Executive Officer Carla Hoorweg stated that the results highlight a growing industry shift toward integrated safety design, with improvements in technologies such as autonomous emergency braking and lane support translating into meaningful real-world protection.
“ANCAP’s testing continues to reinforce a clear message: the safest vehicles are those designed with safety as a system, not a checklist. The top performers this year delivered consistent results across physical crash protection, crash avoidance and vulnerable road user safety, rather than relying on strength in a single area.
“We are also seeing increasing alignment between ANCAP’s test requirements and the safety technologies that genuinely matter on Australian and New Zealand roads. Improvements in autonomous emergency braking, lane support, and driver monitoring systems are translating into more robust protection,” Hoorweg said.
Elon Musk’s xAI brings 1GW Colossus 2 AI training cluster online
Tesla AI5 chip nears completion, Elon Musk teases 9-month development cadence
