Investor's Corner
Tesla patents AR-based system for faster, more accurate vehicle production
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.
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.
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- An illustration of Tesla’s AR-augmented production system. [Credit: US Patent Office]
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- An illustration of Tesla’s AR-augmented production system. [Credit: US Patent Office]
An illustration of Tesla’s AR-augmented production system. [Credit: US Patent Office]
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“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.”
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.
SpaceX’s massive investment in AI will make it a big winner, Argus Research said after the company’s successful earnings call last week.
The firm also upgraded shares to a Buy from Hold and set a $160 price target.
SpaceX (NASDAQ: SPCX) is currently recovering from its heavy AI infrastructure investments, as it spent nearly $16 billion in Q2 alone. The company did this primarily by monetizing high-demand GPU compute capacity at a much faster pace than traditional data center economics would suggest.
Company CFO Bret Johnsen said that SpaceX would be able to pay back anything on new deployments within a year.
There are plenty of ways the company can do this:
Leasing excess compute capacity through contracts
SpaceX has already built Colossus and Colossus II, largely for its own model training. However, much of that capacity is already rented out to third parties. It already has major deals with Anthropic, Google, and Reflection AI. These partnerships are adding billions per month to SpaceX’s spreadsheet.
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High utilization driven by industry-wide scarcity
The demand for advanced AI training and inference capacity continues to exceed what is available for use. SpaceX can fill new racks quickly after they come online, so the capital deployed converts into revenue with minimal idle time.
Additionally, management and outside observers have described the new compute capital as behaving more like a cost-of-goods-sold than traditional multi-year capex, especially because of this rapid monetization pattern.
Capacity has already scaled from ~0.4 GW a year to 1.4 GW annually by the end of Q2. There are targets of more than 2 GW by year-end.
High incremental margins on the rental business once capacity is online
GPU cloud providers often operate at strong gross margins. SpaceX can monetize capacity that was already partially built or can be added efficiently. This means that incremental EBITDA margins on the rental revenue are usually high. This accelerates cash recovery relative to the gross capital outlay.
Parallel monetization of its own AI software and applications
Beyond pure infrastructure rental, SpaceX also generates revenue from Grok through subscriptions and usage, from X through ads, data, and other related services, enterprise APIs, and the planned integration of the Cursor coding tools acquisition.
These application layers ride on the same compute infrastructure and provide additional high-margin streams that could offset build-out costs. AI-segment revenue overall rose sharply to about $2.6 billion in Q2, according to Motley Fool. This was driven primarily by the infrastructure contracts, but the software side is also partially responsible.
Efficient, large-scale deployment and vertical integration advantages
SpaceX has emphasized the rapid construction of power and cooling infrastructure and favorable cost-per-megawatt economics relative to industry benchmarks in some disclosures.
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Combined with its ability to scale capacity aggressively and the fact that many contracts start generating revenue within months of capacity coming online, the effective payback compresses dramatically compared with more conventional multi-year data-center projects.
SpaceX’s dominant near-term recovery path will turn the AI clusters into a hyperscale-style compute rental business for other leading AI companies while still using a portion for internal models.
Elon Musk
Another Tesla SpaceX merger prediction by ARK Invest has Elon Musk talking
Elon Musk again denies a Tesla China split as new SpaceX merger speculation resurfaces quickly.
Elon Musk restated that Tesla has no plans to separate its China business from the rest of the company, responding to a new round of merger speculation from ARK Invest.
On the firm’s “Brainstorm” podcast, Cathie Wood’s team, including chief futurist Brett Winton and research director Nick Grous, argued a Tesla and SpaceX combination remains likely, with an announcement possible before the end of the year even if the deal itself would not close that quickly. Winton called Tesla’s Shanghai operations a “small ish wrinkle” for a merger rather than a real obstacle, since SpaceX’s national security work with the U.S. government sits uneasily next to Tesla’s manufacturing base in China.
Musk pushed back on the framing directly. “China is awesome. I strongly encourage people to visit,” he wrote on X. He also repeated language he first used in late July, when the Wall Street Journal reported that Tesla executives had been told to prepare for a possible spinoff, sale, or closure of the China business ahead of a SpaceX tie up. Musk called that report “absurdly fake news” at the time, adding that a separation had “never even come up in a discussion ever,” a line he echoed again this week.
The repeated denial has not settled the underlying question, because Shanghai’s role in Tesla’s business is exactly what makes a merger complicated. Gigafactory Shanghai still ships more than half of Tesla’s global deliveries and functions as the company’s main export hub for Europe and Asia. Teslarati previously reported on Musk’s initial denial, and the merger conversation itself has been building since SpaceX’s IPO gave it public shares to use as acquisition currency.
Wedbush’s Dan Ives has pegged the odds of a Tesla SpaceX merger at 80 to 90 percent by early 2027, and ARK’s prediction of a year end announcement adds another data point to that timeline, even as Musk keeps rejecting the specific mechanics reporters have described. Neither position rules out the other. Musk can deny a China spinoff was ever discussed while analysts still expect some form of combination to move forward, since ARK and Ives are both describing convergence at the corporate level, not necessarily the internal restructuring the Journal described in July.
For now, Tesla’s China business remains intact, and Musk’s comments this week make clear he has no interest in publicly walking that position back, no matter how often the merger question resurfaces.
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Elon Musk
The real reason Elon Musk wants every car connected to space
Elon Musk says all cars will eventually need Starlink to handle massive AI bandwidth demand.
Elon Musk is making the case that satellite internet, not fiber or cellular towers, will end up wired into every car on the road. In a string of posts on X, the SpaceX CEO wrote that all cars will have Starlink in the future and called satellite connectivity the only way to get super high bandwidth to billions of vehicles.
The posts started with Musk endorsing a Cloudflare forecast that traffic generated by autonomous AI agents will soon dwarf traffic generated by humans browsing the internet, a shift he described as not a close call at all. From there he narrowed the argument to infrastructure, writing that the only system that can support the insanely fast bandwidth growth needed by AI is Starlink, before extending the logic to cars specifically.
AI agentic Internet traffic will obviously VASTLY exceed human usage. Not a close call at all.
Cloudflare’s forecast is accurate. https://t.co/VztgrinN5k pic.twitter.com/Wo4FiRKjPU
— Elon Musk (@elonmusk) August 9, 2026
The timing lines up with Tesla’s own hardware decisions. On July 20, Tesla confirmed the Cybercab would ship with a Starlink V5 terminal built into its roof, the first time the company had put satellite hardware in a production vehicle. A day later, Tesla’s head of AI, Ashok Elluswamy, explained the connection wasn’t there for safety and that Cybercab’s driving stack runs entirely on onboard cameras and compute, while the satellite link exists for navigation, customer service, and fleet management instead. Musk followed with his own post about the feature, saying riders would be able to watch 4K streaming video during rides.
By July 22, Musk had already said Starlink would extend beyond Cybercab to Tesla’s full lineup. Sunday’s posts push that same logic outward again, this time framed as a requirement across the industry rather than a feature specific to Tesla, and tied directly to the bandwidth AI systems are expected to consume.
SpaceX’s newest Starmind will make earth data centers obsolete
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The AI argument has been building on SpaceX’s side for months. The company has an FCC filing pending for a third generation Starlink constellation, and it has separately proposed Starmind, a constellation of up to a million satellites designed to run AI computation directly in orbit rather than just relay data. Musk has said he expects space to become the cheapest place to deploy AI compute within two to three years. Starlink and Starmind serve different jobs inside that vision, one moving data and the other processing it, but Sunday’s posts treat vehicles as one more category of hardware that will eventually need both.
None of this changes anything for Tesla owners today. Cars already on the road keep running on LTE and Wi-Fi, and Tesla hasn’t outlined a retrofit path for existing vehicles. The July 22 commitment applies to future production, not the fleet already delivered. What Musk added on Sunday is the reasoning: satellite connectivity isn’t a Cybercab novelty, it’s a bet that ground based networks won’t keep up with how much data cars, robots, and AI systems are about to generate.
SpaceX AI investment gamble will make it a big winner, firm says
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