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Tesla patents AR-based system for faster, more accurate vehicle production

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Being a company led by an unorthodox CEO with roots in Silicon Valley, Tesla is on the bleeding edge of the automotive market. Tech is evident in Tesla’s DNA, from the automation in its factories to the deep integration of software on its electric vehicles. If a recently published patent is any indication, even more tech-driven solutions are coming to Tesla’s production lines.

A recent patent, dubbed as “Augmented Reality Application for Manufacturing,” was published last Thursday. In the description of the patent, Tesla noted that existing automotive manufacturing techniques are time-consuming and still require a notable amount of manual calibration and inspection. An example of this is the practice of marking joints and/or inspecting dimensional accuracy of car components by having workers manually overlay plastic molds over a sheet metal object to mark certain parts. These processes take a lot of time and effort, resulting in extra operational costs.

Tesla’s solution is rather simple. Instead of using manual processes to perform tasks that include setup, configuration, calibration, and quality inspection, it would be better to utilize available technologies to make operations faster and more precise. One of these technologies is computer vision and augmented reality tools.

A flow diagram illustrating an embodiment of a process for applying augmented reality to manufacturing. [Credit: US Patent Office]

Tesla’s patent uses AR applications and computer vision to “identify an object of interest and the relationship between a user and the object.” The AR device captures a live view of an object, determines the location of the device, as well as the type of the object of interest. By using this system, workers will be able to view instant data about the components they are working on.

“(For example), the AR device identifies that the object of interest is a right-hand front shock tower of a vehicle. The AR device then overlays data corresponding to features of the object of interest, such as mechanical joints, interfaces with other parts, thickness of e-coating, etc. on top of the view of the object of interest. Examples of the joint features include spot welds, self-pierced rivets, laser welds, structural adhesive, and sealers, among others.

“As the user moves around the object, the view of the object from the perspective of the AR device and the overlaid data of the detected features adjust accordingly. The user can also interact with the AR device. For example, a user can display information on each of the identified features. In some embodiments, for example, the AR device displays the tolerances associated with each detected feature, such as the location of a spot weld or hole.”

Apart from allowing production to move faster, the AR-based system could also be used for quality inspections. Tesla even noted that such a system could be tapped to determine if panels in vehicles are within tolerances, and if holes in the electric cars’ frames are drilled or punched at the correct location.

An illustration of Tesla’s AR-augmented production system. [Credit: US Patent Office]

“There are many practical applications for the augmented reality (AR) manufacturing techniques discussed herein. In some embodiments, the AR device is used to program a robot to assemble one or more parts including identifying and marking the precise location and order of welds, self-pierced rivets, laser welds, adhesives, sealers, holes, fasteners, or other mechanical joints, etc. As another example, the AR device can be used to inspect the quality of the assembly for a vehicle such as whether the locations of welds are correct, whether the interfaces between parts such as body panels are within tolerances, whether holes are drilled or punched at the correct location, whether the fit and finish of assembly is correct, etc.

“In some embodiments, vision recognition is utilized. Individual sheet metal components and/or assemblies that are or will be part of the body-in-white (also known as the structural frame or body) are recognized. Once the component/system has been identified, computer-aided design (CAD) information (e.g., information and/or symbols associated with the mechanical joints) is aligned/scaled and rendered on corresponding identified physical model components. The application of the disclosed techniques applies to many different contexts of manufacturing.

“For example, the AR device can be used to map the quality of a coating on an automotive part such as determining the thickness of an e-coating on a vehicle body and identifying problem areas that are difficult to coat. In some embodiments, the AR device is used to map out a factory floor and to identify the precise location and orientation robots should be installed at to build out an assembly line. The robots are positioned based on the AR device such that the installed robots will not interfere with each other or other obstructions in the environment.”

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An AR-based system that augments production fits very well with Tesla’s reputation as a car maker that never stays stagnant. During an interview at Gigafactory 1, Tesla President of Automotive Jerome Guillen mentioned that the company’s battery cells — while already industry-leading — are always evolving. Elon Musk echoed this idea as well, when he noted that improvements to Tesla’s electric cars are being rolled out as soon as they are ready. Optimizations such as the use of AR and computer vision in the production line is yet another example.

Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

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Investor's Corner

Tesla Robotaxi gets a massive upgrade in Nevada

Nevada regulators just approved a massive expansion of Tesla’s robotaxi fleet across the entire county.

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Concept art of a Tesla Cybercab in Las Vegas Strip as rendered via Grok

Tesla’s robotaxi footprint in Nevada just grew by roughly 500 times in a single regulatory vote.

The Nevada Transportation Authority approved Tesla’s full Autonomous Vehicle Network Company permit on Thursday, clearing the way for the company to deploy up to 5,000 driverless vehicles across Clark County over the next 12 months. The decision came during a four hour general session meeting that Tesla investor Sawyer Merritt watched live and reported on X, noting the vote replaces the interim order that had limited Tesla to just 10 robotaxis on a narrow stretch of the Las Vegas Strip.

That earlier cap, covered here after it surfaced on August 13, came with restrictions that looked stricter than what Tesla runs in Austin: a 45 mph speed ceiling, no airport pickups, and a geofence confined to the Strip corridor. The new approval extends Tesla’s operating authority to all of Clark County, with room to request an even wider geofence across the state.

Tesla representatives at the meeting said they have no intention of putting 5,000 cars on the road right away. Commercial rides are expected to start within 30 days, pending vehicle inspections, insurance filings, and fare approval, the standard steps every robotaxi operator in Nevada has had to clear.

Tesla’s own Robotaxi account replied to the news with a short line, The golden future is upon us.

The timing lines up with Tesla’s broader robotaxi push this month. The company is preparing to open Cybercab rides to the public in Austin as soon as this month, and it opened a sweepstakes for riders to win a seat at the launch event. Tesla filed its original application for a 5,000 vehicle Nevada fleet back in June, a request regulators trimmed to 10 vehicles when they issued the interim order in July. Thursday’s vote effectively grants the number Tesla asked for from the start.

Zoox, the Amazon owned robotaxi operator, has run in Nevada since 2025 and was capped at 100 vehicles before Thursday’s decision. Tesla’s new ceiling puts it well ahead of that comparison on paper, though the company has said its actual fleet size will depend on how quickly FSD v15 rolls out, the software update executives have called the gateway to scaling unsupervised robotaxi operations nationwide.

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SpaceX’s next trillion dollar bet has nothing to do with rockets, Musk tells staff

Elon Musk told SpaceX staff AI revenue will soon dwarf rockets and Starlink combined entirely.

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Elon Musk told SpaceX employees this week that artificial intelligence, not rockets, will soon carry the company’s revenue. In a roughly 29 minute internal address posted on SpaceX’s X account on Tuesday, Musk said AI revenue will pass every other line of business at SpaceX “probably in September” and pull further ahead by the fourth quarter.

The numbers he gave are specific. SpaceX currently runs 1.4 gigawatts of AI compute capacity. Musk wants that at 10 gigawatts by the end of 2027, a jump he tied directly to revenue: “if we bring 10GW of AI online by the end of next year, it will be $300 billion to $500 billion a year in revenue.” He called those “big numbers,” which undersells a projection larger than what most countries produce in a year.

Musk went further on where AI fits into SpaceX’s future. “Probably in four or five years, AI will be 99% of the value of SpaceX,” he told staff, adding that digital intelligence would eventually run “a trillion times” ahead of biological intelligence as computing scales. He tied that growth to the company’s founding mission, telling employees “we must win on AI, because the future is overwhelmingly AI and robots,” with the payoff meant to help fund Starship and a Mars program that increasingly runs through Terafab, the joint Tesla, SpaceX and xAI chip plant.

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None of this is entirely new territory. SpaceX told investors much the same story during its first earnings call as a public company on August 4, where Musk moved the company’s $1 trillion revenue target up a year to 2030 and said Starlink could someday carry a majority of the world’s internet. What the all hands video adds is a hard deadline and a specific power figure Musk had not given publicly before, along with a franker pitch to his own workforce that AI, not launch cadence, is now the thing SpaceX is betting its future on.

The AI revenue itself is not coming from SpaceX training its own models. It is largely Starlink acting as the network layer for xAI’s workloads, plus SpaceX renting out compute capacity directly, the same approach behind the roughly $16 billion the company spent on AI infrastructure in a single quarter.

Musk closed the video with a pitch aimed at recruiting and retention rather than investors, telling employees that anyone who helps SpaceX win the AI race will eventually get the chance to go to the moon or Mars themselves. Whether SpaceX can turn 1.4 gigawatts into 10 in seventeen months is the more immediate question, and one that will show up in quarterly numbers well before anyone leaves Earth.

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Tesla has one big financial question to answer for investors: Morgan Stanley

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Credit: Tesla

In a new note to investors on Tuesday, Morgan Stanley analyst Andrew Percoco said that Tesla has one big financial question to answer for investors regarding its Robotaxi rollout, Full Self-Driving software, and Optimus.

Percoco said in the note that, for the most part, investors are still very positive about the direction the company is headed. However, there are some things the firm would like to see, and they have to do with financials.

Tesla (TSLA) Q2 2026 earnings results: miss on EPS, beat on revenue

Tesla bulls are more than convinced that the company’s Full Self-Driving software is proof it can develop physical AI. Financially, however, there are still some questions, especially on elevated spending, which CEO Elon Musk said would occur as the company works to roll out Robotaxi faster and continue developing its Optimus robot.

The latter two are where Tesla will have to prove progress to investors, as Percoco writes that both projects “will require clearer evidence that Robotaxi is scaling and more tangible Optimus proof points to support the ROI on elevated capex.”

Percoco said the second quarter earnings call did not change his long-term thesis of where Tesla is positioned in the AI race, which is out in front. However, there are concerns that weaker gross margins and higher R&D spend will stress financials, and that has “sharpened our (and investors’) focus on measurable progress across Robotaxi and Optimus.”

Additionally, Robotaxi still needs to be proven with more operation in existing cities while maintaining safety but improving how many rides it gives in any given time, he said. For Optimus, Percoco wrote that he is “still looking for evidence beyond commentary around SOP.”

Morgan Stanley put Percoco in charge of covering Tesla after long-time analyst Adam Jonas transitioned to the automotive side.

Currently, Morgan Stanley has a $415 price target on Tesla and a ‘Hold’ rating on the stock. It is trading at around $330 at the time of publication, which was 2:30 P.M. on the East Coast.

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