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Tesla is patenting a clever way to train Autopilot with augmented camera images

Tesla Autopilot construction zone lane (Credit: YouTube/Cf Tesla)

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Tesla is currently tackling what could only be described as its biggest challenge to date. In his Master Plan, Part Deux, CEO Elon Musk envisioned a fleet of zero-emissions vehicles that are capable of driving on their own. Tesla has made steps towards this goal with improvements and refinements to its Autopilot and Full Self-Driving suites, but a lot of work remains to be done.

As noted by Tesla during its Autonomy Day presentation last year, attaining Full Self-Driving is largely a matter of training the neural networks used by the company. Tesla adopts what could be described as a somewhat organic approach for autonomy, with the company using a system that is centered on cameras and artificial intelligence — the equivalent of a human primarily using the eyes and brain to drive.

Tesla’s camera-centric approach may be quite controversial due to Elon Musk’s strong stance against LiDAR, but it is gaining ground, with other autonomous vehicle companies such as MobilEye developing FSD systems that rely primarily on visual data and a trained neural network. This approach does come with its challenges, as training neural networks requires tons of data. Tesla emphasized this point as much during its Autonomy Day presentation.

With this in mind, it is pertinent for the electric car maker to train its neural networks in a way that is as efficient as possible with zero compromises. To help accomplish this, Tesla seems to be looking into the utilization of augmented data, as described in a recently published patent titled “Systems and Methods for Training Machine Models with Augmented Data.”

A block diagram of an environment for computer model training. (Credit: Patentscope.wipo.int)

Teslas are equipped with a suite of cameras that provide 360-degree visual coverage for the vehicle. In the patent’s description, Tesla noted that images used for neural network training are usually captured by various sensors, which, at times, have different characteristics. An example of this may lie in a Tesla’s three forward-facing cameras, each of which has a different field of view and range as the other two.

Tesla’s recent patent describes a system that allows the company to process these images in an optimized manner. Part of how this is done is through augmentation, which opens the doors to flexible and widespread neural network training, even when it involves vehicles equipped with differently-specced cameras. The electric car maker describes this process as such:

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“Augmentation may provide generalization and greater robustness to the model prediction, particularly when images are clouded, occluded, or otherwise do not provide clear views of the detectable objects. These approaches may be particularly useful for object detection and in autonomous vehicles. This approach may also be beneficial for other situations in which the same camera configurations may be deployed to many devices. Since these devices may have a consistent set of sensors in a consistent orientation, the training data may be collected with a given configuration, a model may be trained with augmented data from the collected training data, and the trained model may be deployed to devices having the same configuration.”

Among the most notable aspects of Tesla’s recent patent is the use of “cutouts,” which allow Tesla’s neural networks to be trained using an optimized set of images. This was something that was discussed by former Tesla Autopilot engineer Eshak Mir in a Third Row Podcast interview, where he hinted at a system adopted in the electric car maker’s ongoing Autopilot rewrite that helped lay out “all the camera images” from a vehicle “into one view.” Such a process has the potential to help Tesla with 3D labeling, especially since the images used for neural network training are stitched together. Tesla’s patent seems to reference a system that is very similar to that described by the former Autopilot engineer.

“As a further example, the images may be augmented with a“cutout” function that removes a portion of the original image. The removed portion of the image may then be replaced with other image content, such as a specified color, blur, noise, or from another image. The number, size, region, and replacement content for cutouts may be varied and may be based on the label of the image (e.g., the region of interest in the image, or a bounding box for an object).”

Tesla is aiming to release a feature-complete version of its Full Self-Driving suite as soon as possible. Elon Musk remains optimistic about this, despite the company missing its initial timeline that was set at the end of 2019. That being said, Elon Musk did mention previously that Tesla is working on a foundational rewrite of Autopilot. In a tweet early last month, Musk stated that an essential part of the rewrite involves work on Autopilot’s core foundation code and 3D labeling. Once done, the CEO indicated that additional functionalities could be rolled out quickly. This recent patent, if any, seems to give a glimpse at how these improvements are being done.

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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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SpaceX Starship just nailed something it’s never done before

SpaceX’s Starship flew successfully Friday, landing both stages and deploying its first Starlink V3 satellites.

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Starship’s thirteenth test flight delivered exactly what SpaceX needed with a clean liftoff, two successful stage recoveries, and the first real payload the vehicle has ever carried to space. Booster 20 and Ship 40 lifted off at 5:51 p.m. CT from Starbase, and by the time the mission wrapped roughly an hour later, both halves of the rocket had done exactly what they were supposed to do.

Booster 20 separated from Ship 40 a few minutes into the flight and stuck a controlled splashdown in the Gulf of Mexico about six minutes after liftoff. That is a meaningful turnaround from Flight 12 in May, when the booster lost several engines during its boostback burn before a hard water landing attempt.


Starship 40’s performance was arguably the bigger win. The vehicle deployed the first 20 operational Starlink V3 satellites Starship has ever carried, then flew a suborbital arc to a landing in the Indian Ocean that SpaceX commentator Dan Huot called the company’s softest splashdown yet. “This is a dream scenario for this team that’s trying to get this heat shield data,” Huot said on the live broadcast, according to Space.com’s live coverage. “I’m a little over the moon right now. Wow. Lucky number 13.”

Unlike the mass simulators SpaceX flew on Flight 12, these were production Starlink V3 satellites, meant to extend solar arrays and antennas and attempt to link with the broader constellation before reentering minutes later. Getting real hardware through a full deploy sequence on only the second flight of the V3 generation keeps Starship on schedule for the payload work NASA is counting on for future Artemis lunar landings.

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— TESLARATI (@Teslarati) July 25, 2026

The flight also arrives at a moment when SpaceX needed a win. SPCX has traded below its $135 IPO price since mid-July, as Teslarati reported when the mission slipped to Friday, and short interest has climbed to roughly a third of the tradable float. A clean flight will not fix a balance sheet, but it does answer the one question SpaceX absolutely needed answered this week: whether the fixes made after the July 16 abort would hold up under real flight conditions. They did, on both stages, on the first try after the redesign.

SpaceX has not set a target date for Flight 14, though the company has said it wants to push toward an orbital attempt on the next mission. After Friday, that goal looks a lot more within reach.

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Tesla’s Supercharger Diner probably just secured more locations

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tesla diner
Credit: Tesla

Tesla’s Supercharger Diner in Los Angeles dominated the company’s global usage rankings after just one year, proving the concept is more than just a one-off novelty location that will fade away.

The performance could incite the company to build more locations, something that CEO Elon Musk has hinted at for some time.

Tesla’s Supercharger Diner delivered 21.2 GWh of energy in its first year of operation, the company’s head of Charging, Max de Zegher, revealed on X. Of the top 10 most utilized Supercharger locations in Tesla’s global infrastructure, the Diner in Los Angeles was the most used by drivers, and it wasn’t particularly close:

On its launch day one year ago, nobody was too sure what the Tesla Diner would be about. It seemed like an interesting concept, and considering it had been in the works for years, it was a highly anticipated launch that many were looking forward to.

Based on its success, we could see additional Diners with Superchargers built throughout the United States, and potentially beyond. Musk has said on several occasions that the company would be willing to bring the Diner idea to more markets.

Tesla makes major change at Supercharger Diner amid epic demand

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Of the markets that Musk has mentioned, both Palo Alto and Austin have come to be perceived as ideal selections. However, there are no concrete plans as of now to build new Supercharger Diners anywhere; the location on Santa Monica Boulevard will remain the exclusive spot to pick up Tesla-inspired eats, at least for the time being.

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Investor's Corner

Tesla short sellers win big after shares fall after earnings

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A red Tesla Roadster driving around a turn
(Credit: Tesla)

Tesla short sellers won big following the company’s massive fall on Wall Street after it reported subpar Earnings on Wednesday.

Tesla short sellers collected about $4.12 billion in single-day profits on Thursday, according to BloombergShares fell as much as 15 percent during Thursday’s session. It closed as one of the worst days for Tesla on Wall Street in the past three years.

Investors sold off the stock after Tesla said it would aggressively direct its spending toward AI and its Optimus robot project. The company had record revenues, which were driven by one of the strongest quarters in terms of vehicle deliveries in company history.

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However, it missed EPS estimates by reporting just $0.33, a far cry from the $0.53 analysts expected.

S3 Partners reported that about 3 percent of Tesla’s outstanding stock is sold short. Managing Director at S3, Ihor Dusaniwsky, provided the short seller’s potential profit, as well as another figure: shorts have likely had paper gains of $8.92 billion this year, as Tesla shares are down 30 percent in 2026.

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

Tesla has burned short sellers many times in the past, but the company’s latest Earnings Call was a chance for those skeptics to taste some payback. Although the company gave some very transparent information regarding future projects, the rollout of Robotaxi, Optimus, and Semi, many investors took their profits on Thursday.

Notable short sellers like Michael Burry have been transparent about their skepticism around Tesla shares. Burry just revealed three weeks ago that he had opened up a new short on the stock, stating he shorted Tesla shares at $416.22. “Happy it jumped back to this level,” he said in a blog post.

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At the time of publication, Tesla shares were down about 3 percent and the stock was trading at $309.92.

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