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Tesla is patenting a clever way to train Autopilot with augmented camera images
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.”
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:
“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.
News
Tesla Model Y Standard Long Range RWD launches in Europe
The update was announced by Tesla Europe & Middle East in a post on its official social media account on X.
Tesla has expanded the Model Y lineup in Europe with the introduction of the Standard Long Range RWD variant, which offers an impressive 657 km of WLTP range.
The update was announced by Tesla Europe & Middle East in a post on its official social media account on X.
Model Y Standard Long Range RWD Details
Tesla Europe & Middle East highlighted some of the Model Y Standard Long Range RWD’s most notable specs, from its 657 km of WLTP range to its 2,118 liters of cargo volume. More importantly, Tesla also noted that the newly released variant only consumes 12.7 kWh per 100 km, making it the most efficient Model Y to date.
The Model Y Standard provides a lower entry point for consumers who wish to enter the Tesla ecosystem at the lowest possible price. While the Model 3 Standard is still more affordable, some consumers might prefer the Model Y Standard due to its larger size and crossover form factor. The fact that the Model Y Standard is equipped with Tesla’s AI4 computer also makes it ready for FSD’s eventual rollout to the region.
Top Gear’s Model Y Standard review
Top Gear‘s recent review of the Tesla Model Y Standard highlighted some of the vehicle’s most notable features, such as its impressive real-world range, stellar infotainment system, and spacious interior. As per the publication, the Model Y Standard still retains a lot of what makes Tesla’s vehicles well-rounded, even if it’s been equipped with a simplified interior.
Top Gear compared the Model Y Standard to its rivals in the same segment. “The introduction of the Standard trim brings the Model Y in line with the entry price of most of its closest competition. In fact, it’s actually cheaper than a Peugeot e-3008 and costs £5k less than an entry-level Audi Q4 e-tron. It also makes the Ford Mustang Mach-E look a little short with its higher entry price and worse range,” the publication wrote.
Elon Musk
Elon Musk’s xAI bets $20B on Mississippi with 2GW AI data center project
The project is expected to create hundreds of permanent jobs, dramatically expand xAI’s computing capacity, and further cement the Mid-South as a growing hub for AI infrastructure.
Elon Musk’s xAI plans to pour more than $20 billion into a massive new data center campus in Southaven, Mississippi, marking the largest single economic development project in the state’s history.
The project is expected to create hundreds of permanent jobs, dramatically expand xAI’s computing capacity, and further cement the Mid-South as a growing hub for AI infrastructure.
xAI goes MACROHARDRR in Mississippi
xAI has acquired and is retrofitting an existing facility in Southaven to serve as a new data center, which will be known as “MACROHARDRR.” The site sits near a recently acquired power plant and close to one of xAI’s existing data centers in Tennessee, creating a regional cluster designed to support large-scale AI training and inference.
Once completed, the Southaven facility is expected to push the company’s total computing capacity to nearly 2 GW, placing it among the most powerful AI compute installations globally. The data center is scheduled to begin operations in February 2026.
Gov. Tate Reeves shared his optimism about the project in a press release. “This record-shattering $20 billion investment is an amazing start to what is sure to be another incredible year for economic development in Mississippi. Today, Elon Musk is bringing xAI to DeSoto County, a project that will transform the region and bring amazing opportunities to its residents for generations. This is the largest economic development project in Mississippi’s history,” he said.
xAI’s broader AI ambitions
To secure the investment, the Mississippi Development Authority approved xAI for its Data Center Incentive program, which provides sales and use tax exemptions on eligible computing hardware and software. The City of Southaven and DeSoto County are also supporting the project through fee-in-lieu agreements aimed at accelerating development timelines and reducing upfront costs.
Founded in 2023 by Elon Musk, xAI develops advanced artificial intelligence systems focused on large-scale reasoning and generative applications. Its flagship product, Grok, is integrated with the social media platform X, alongside a growing suite of APIs for image generation, voice, and autonomous agents, including offerings tailored for government use.
Elon Musk highlighted xAi’s growth and momentum in a comment about the matter. “xAI is scaling at an immeasurable pace — we are building our third massive data center in the greater Memphis area. MACROHARDRR pushes our Colossus training compute to ~2GW – by far the most powerful AI system on Earth. This is insane execution speed by xAI and the state of Mississippi. We are grateful to Governor Reeves for his support of building xAI at warp speed,” Musk said.
Tesla’s Head of AI, Ashok Elluswamy, says that something that was expected with version 14.3 of the company’s Full Self-Driving platform has already partially shipped with the current build of version 14.2.
Tesla and CEO Elon Musk have teased on several occasions that reasoning will be a big piece of future Full Self-Driving builds, helping bring forth the “sentient” narrative that the company has pushed for these more advanced FSD versions.
Back in October on the Q3 Earnings Call, Musk said:
“With reasoning, it’s literally going to think about which parking spot to pick. It’ll drop you off at the entrance of the store, then go find a parking spot. It’s going to spot empty spots much better than a human. It’s going to use reasoning to solve things.”
Musk said in the same month:
“By v14.3, your car will feel like it is sentient.”
Amazingly, Tesla Full Self-Driving v14.2.2.2, which is the most recent iteration released, is very close to this sentient feeling. However, there are more things that need to be improved, and logic appears to be in the future plans to help with decision-making in general, alongside other refinements and features.
On Thursday evening, Elluswamy revealed that some of the reasoning features have already been rolled out, confirming that it has been added to navigation route changes during construction, as well as with parking options.
He added that “more and more reasoning will ship in Q1.”
🚨 Tesla’s Ashok Elluswamy reveals Nav decisions when encountering construction and parking options contain “some elements of reasoning”
More uses of reasoning will be shipped later this quarter, a big tidbit of info as we wait v14.3 https://t.co/jty8llgsKM
— TESLARATI (@Teslarati) January 9, 2026
Interestingly, parking improvements were hinted at being added in the initial rollout of v14.2 several months ago. These had not rolled out to vehicles quite yet, as they were listed under the future improvements portion of the release notes, but it appears things have already started to make their way to cars in a limited fashion.
Tesla Full Self-Driving v14.2 – Full Review, the Good and the Bad
As reasoning is more involved in more of the Full Self-Driving suite, it is likely we will see cars make better decisions in terms of routing and navigation, which is a big complaint of many owners (including me).
Additionally, the operation as a whole should be smoother and more comfortable to owners, which is hard to believe considering how good it is already. Nevertheless, there are absolutely improvements that need to be made before Tesla can introduce completely unsupervised FSD.
Tesla Model Y Standard Long Range RWD launches in Europe
Elon Musk’s xAI bets $20B on Mississippi with 2GW AI data center project
