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

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Credit: Tesla

Tesla (NASDAQ: TSLA) reported its earnings for the first quarter of 2026 on Wednesday afternoon. Here’s what the company reported compared to what Wall Street analysts expected.

The earnings results come after Tesla reported a massive beat on vehicle deliveries for the second quarter, delivering 489,126 vehicles and building 451,758 cars during the three-month span.

This was a major shock for those on Wall Street as they anticipated somewhere around 400,000 deliveries for the quarter, and showed Tesla still has plenty of demand for its vehicles around the world and in the U.S. despite losing the $7,500 EV Tax Credit last year.

Tesla Q2 2026 Earnings Results

  • Non-GAAP EPS – $0.33 reported vs. $0.53 expected
  • Revenues – $28.236 billion reported vs. $26.4 billion expected
  • Free Cash Flow- -$1.092B
  • Profit -$ 4.751B

Tesla (beat/missed) analyst expectations, so the market response to the company’s quarter is what we will look for next.

Tesla shares closed today down just over 1 percent, trading at $374.01.

In the past, it has been anyone’s guess with what Tesla shares will do after they report earnings. Strong quarters have resulted in sharp drops, while lackluster quarters have seen the stock shoot up considerably.

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Tesla will hold its Q2 2026 Earnings Call in about 90 minutes at 5:30 p.m. on the East Coast. Remarks will be made by CEO Elon Musk and other executives, who will shed some light on the investor questions that we covered earlier this week.

You can stream it below. Additionally, we will be doing our Live Blog on X and Facebook.

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Tesla is about to make parking in busy lots less stressful than ever

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Tesla FSD 14.3 [Credit: TESLARATI)
Tesla FSD 14.3 [Credit: TESLARATI)

Tesla is about to make parking in busy parking lots at businesses and other points of interest less stressful than ever by allowing drivers more control over where they park and how, CEO Elon Musk confirmed on X.

Tesla has been working to improve the parking performance of vehicles utilizing the Full Self-Driving suite, but now it is looking to add more customization, allowing drivers to choose the specific space they park in, but also potentially the orientation the car pulls into the spot:

Musk has reiterated on X twice over the past several weeks that Tesla is working to make things with the FSD suite based more on the driver’s specific preferences and behaviors that were seen in past drives.

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Essentially, it sounds like if you tend to park away from a business to avoid other vehicles, Tesla FSD will soon recognize that preference of yours and start parking further away as well. Additionally, the prospect of assigned parking spaces has been something many owners have voiced concerns about.

Living in a community with assigned parking spaces makes using FSD incredibly difficult as it will rarely park in the correct spot when there are so many to choose from. This is also pertinent in work settings where there are sometimes assigned parking spaces.

The updates to Tesla’s Full Self-Driving suite in terms of listening to driver preferences with parking are also extending to routing. Tesla announced yesterday that with the release of its 2026 Summer Update, it was adding Automatic Navigation and Preferred Routes:

Tesla reveals 2026 Summer Update with crazy fixes to Nav and more

Tesla has always maintained the idea that any human input is bad input, and that, ideally, Tesla Full Self-Driving will always make the right decision. Of course, this is all in theory, but the issue is that so many of Tesla’s interventions have come because it does something that is not necessarily wrong, but perhaps not what the driver would prefer.

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Taking these preferences into account will help Tesla alleviate some of the potentially unnecessary interventions that drivers perform.

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Tesla starts preparing for Optimus in its smartphone app

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Tesla is starting to prepare for the launch of the Optimus robot in its smartphone app, new coding strings show. Elon Musk has referred to Optimus as what will be the greatest-selling product of any kind of all time, and now, Tesla is getting ready for its launch.

Tesla’s smartphone app had several first-time mentions of the Optimus program, according to Tesla App Updates, who intially reported on the appearance. Here’s what they found:

A Dedicated “Robot” Phone Key Authentication

Tesla is working on a Bluetooth Low Energy, or BLE, authentication that is specifically for robots. This does not only apply to Optimus, though, as Robotaxi, which is Tesla’s autonomous ride-hailing platform, might also identify vehicles within the fleet as robots as well.

Tesla shows rapid teardown of Model S and X lines, paving the way for Optimus at Fremont

Essentially, pairing your phone as a key to anything Tesla identifies as a robot to a “whitelist” of authorized devices. Optimus, Robotaxi, or other products that fall into this category will only respond if the device trying to communicate with it is authorized.

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This is a great security feature that will eliminate at least face-value and low-level threats.

Home Data Collection and System Alerts

This appears to be somewhat of a neural network for Optimus within your house. There will be a dedicated screen that asks for consent to collect both video and spatial data while Optimus performs in-home tasks. Everything from vacuuming, washing dishes, dusting, and other activities will be tracked.

There will also be a comprehensive alert system that will track everything from low battery to mechanical issues.

Other Changes

Most of the changes tracked in this particular app update are related to Tesla’s 2026 Summer Update, and include things such as image assets for new features, a preview of the new custom wraps feature, and other unique features.

You can check out our coverage on what is included with the 2026 Summer Update here:

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Tesla reveals 2026 Summer Update with crazy fixes to Nav and more

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