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.
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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
Tesla AI boss reveals how big Optimus is going to get
Tesla’s Optimus chief corrected himself on X, confirming a staggering 10 million robot production target.
![Tesla Optimus Gen 3 [Credit: Tesla]](https://www.teslarati.com/wp-content/uploads/2026/03/tesla-optimus-gen3-diner.jpg)
Tesla’s Optimus program has a new number attached to it, after Ashok Elluswamy, the executive who has run the humanoid robot program since June 2025, posted a three word correction on X Thursday, “Correction, 10 million robots.”
The line clarifies the long term annual capacity Tesla is building toward its planned second Optimus production line at Gigafactory Texas, a figure Musk has cited repeatedly since last year’s shareholder meeting.
The scale is worth noting, because ten million robots a year would mean Tesla building more units annually than most countries sell in new cars. Tesla has framed this as a second line, not the first. The buildout is happening in two phases: a roughly one million unit per year line inside Tesla’s Fremont factory, installed on the floor space vacated when Model S and Model X production ended earlier this year, and a much larger dedicated facility under construction at Giga Texas that broke ground on its first steel structure in May. That Texas facility is the one Elluswamy’s correction refers to, and is expected to reach volume production sometime in 2027.
Correction, 10 million robots https://t.co/0z4nyQNTzp
— Ashok Elluswamy (@aelluswamy) July 30, 2026
Tesla Optimus project fires up as Musk sees production line progress
Elluswamy took over Optimus from Milan Kovac last summer and has spent the months since talking up the program’s trajectory. Elon Musk has also floated the ten million figure at Tesla’s 2025 shareholder meeting.
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Ending Model S and Model X production to make room for the first Optimus line was one of the more consequential manufacturing decisions in the company’s recent history, retiring two flagship vehicles in favor of a robot that has yet to enter mass production. Musk has previously estimated per unit production costs at $20,000 to $25,000 once Tesla reaches a million units a year, though he hasn’t said what that cost looks like at ten times the volume.
The Trump Administration today made several key moves to help with the deployment of autonomous vehicles by cutting overreaching red tape that has stifled growth and innovation for years.
The moves, which were put forth by the National Highway Traffic Safety Administration (NHTSA), aim to grant temporary exemptions to at least one company currently, although that could expand in the coming months. Additionally, it will work with organizations to develop standards and a sound but efficient regulatory landscape.
Zoox is the only company mentioned explicitly by the Trump Administration in its press release announcing the new terms today. They will receive a temporary two-year exemption that will allow the commercial deployment of up to 2,500 vehicles annually for two years.
There is a potential exemption for Robomart, Inc., which “requests a temporary exemption from certain FMVSS No. 500 requirements for a low-speed vehicle operated by an ADS without a human driver onboard. NHTSA will publish a separate notice seeking public comment on its merits once the initial evaluation is complete,” the agency said.
Here are the five new terms that Secretary Sean Duffy has implemented through the NHTSA today:
- Allow Zoox to commercially deploy its robotaxis through a temporary exemption.
This temporary exemption will allow the commercial deployment of up to 2,500 vehicles annually for two years, subject to an enhanced, adaptable oversight structure that can evolve as Zoox’s technology advances. - Accelerate development of first-ever AV performance standards through a partnership with SAE Industry Technologies Consortia (ITC).
This partnership will fund a three-year, $5 million “A2SCEND” consortium, bringing together experts to gather data and accelerate creation of the first-ever AV performance standards. This project will inform a single national standard for AV safety to eliminate the patchwork regulatory landscape that has stifled innovation for years. - Publish an interim final rule that allows vehicles manufactured prior to an exemption to be eligible for a commercial deployment exemption.
This rule will modernize the application process and improve access to exemptions for innovators, including AV developers, by granting the NHTSA Administrator the discretion to apply temporary exemptions to vehicles manufactured prior to the effective date of an exemption grant. - Streamline the application process for Part 555 exemptions by updating guidance and soliciting feedback from the public.
By updating the Part 555 exemption process—which allows automakers to temporarily sell a limited number of non-compliant vehicles, primarily to test new technologies—NHTSA is aiming to create a more flexible oversight structure for exemptions and summarize recent AV framework activities, including expanded exemption pathways, streamlined crash reporting, and ongoing efforts to modernize Federal Motor Vehicle Safety Standards (FMVSS). - Establish a new Federal Docket for public feedback on NHTSA’s updated safe AV development and deployment guidance.
NHTSA is updating its technical guidance for AVs for the first time since 2017—focusing on key safety areas like emergency responder interactions, safety management systems, remote assistance, and post-crash behavior to help the industry scale up driverless deployments safely.
Additionally, the NHTSA said it has modernized some safety standards by proposing updates to:
- FMVSS 102 – Transmission shifting
- FMVSS 103/104 – Windshield defrosting and wiping
- FMVSS 110 – Tire placards
- FMVSS 135 – Braking systems
- FMVSS 101 – Controls and displays
- FMVSS 108 – Vehicle lighting
- FMVSS 111 – Mirrors and rearview display
- FMVSS 126 – Electronic stability control systems
- FMVSS 201/208 – Sun visors and warning labels
These changes aim to make the regulatory process for autonomous vehicles more streamlined and efficient, which could help the U.S. gain dominance over autonomous vehicle systems moving forward.
Elon Musk is, in many respects, one of the biggest and most influential figures in modern-day artificial intelligence.
Given that Tesla, SpaceX, and xAI are all looked at in their respective fields as leaders to an extent, each of them has a heavy influence on the future of AI, even though two of them are not thought of, at face value, as AI companies.
Musk has grand expectations for what is to come with AI, not only as a form of assistance to make human lives easier, but to make humans multiplanetary and solve some of the biggest issues that face us today. But even he is astounded by AI’s pace of progress.
He believes that in two years, AI will be so mind-blowing it might be unrecognizable.
Given that AI from 2 years ago feels so old that it should be in a museum, then obviously AI 2 years from now will be mind-blowing https://t.co/TcsKZ8o8OE
— Elon Musk (@elonmusk) July 30, 2026
This progress can be seen in a variety of ways, but perhaps the most popular way people have shown AI’s progress, especially on social media, is through an incredibly arbitrary way of watching Will Smith eat spaghetti:
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The progression in AI of Will Smith eating spaghetti (2023 – 2026) pic.twitter.com/VDv82mB5gs
— internet hall of fame (@InternetH0F) February 10, 2026
This is a great way to show people how AI is improving, especially from a perspective that examines how it can manufacture images and video from prompts. AI is an incredibly complex concept, however, and it goes much deeper than Will Smith eating Italian food.
Musk’s most widely adopted method of AI is likely Tesla Full Self-Driving, which impacts millions of people as they utilize it to increase safety with their travel. Musk has routinely pushed incredibly aggressive timelines for self-driving, especially unsupervised.
Perhaps this perspective is why he feels that things will be solved in a timeframe that is much more aggressive than most of us would think. Regardless, the progress of AI is moving fast, and it seems that Musk’s expectations for it could be high.
But if it can actually achieve full-length motion pictures and even more realistic production value, it will be hard to distinguish between reality and AI very soon.
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![Tesla Optimus Gen 3 [Credit: Tesla]](https://www.teslarati.com/wp-content/uploads/2026/03/tesla-optimus-gen3-diner-80x80.jpg)
Tesla AI boss reveals how big Optimus is going to get
Autonomous vehicle red tape gets slashed by Trump Administration
