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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.
Tesla has revealed plans through permit submissions for a massive Robotaxi charging hub in Austin, Texas.
Tesla plans to build the Supercharger hub in multiple phases, with the second phase potentially introducing wireless induction charging, something the company has been developing for the Robotaxi fleet.
Initially, 48 Tesla Robotaxi-geared Superchargers will be built on a lot just across from the St. Elmo, Texas, Service Center. There are about 80 additional spots that will not be impacted by phase 1 of the construction process.
Filings show that the second phase of the project will turn those 80 additional spots into wireless charging for Robotaxi, but it might be an error. The Key Notes state that item 3 is listed as “V4 Charging Cabinet to Support 80 Wireless Chargers in Phase 2. However, the drawings point to V3 Cabinets that are already tied to Superchargers:
There are roughly 128 total spots in the lot, but it is unclear if they will all be used for charging based on what appears to be some sort of typo in the blueprint.
A new Robotaxi fleet charging hub is coming soon to Austin, Texas!!
Permits have been filed for the installation of 48 (V3) stalls in a vehicle storage lot across the road from Tesla’s St Elmo service center. pic.twitter.com/xwRgSWDqht
— MarcoRP (@MarcoRPi1) August 18, 2026
This is among the first Robotaxi charging hubs Tesla has started to develop, as it currently has four others planned throughout various areas: one in Phoenix, one in San Antonio, another in Irving, which will serve the Dallas-Fort Worth area, and another in Las Vegas.
These projects are necessary as Tesla expands its Robotaxi program. Now that preparations have started for the public launch of Cybercab, Robotaxi will likely be expanding aggressively, especially over the next two to three years.
Last night, The Information reported that Tesla was planning to launch Cybercab as soon as the end of August. Hours later, Tesla then announced it was launching a competition for fans to potentially ride in Cybercab during its first public rides.
Tesla’s plan to expand its charging infrastructure in the regions where Robotaxi will initially operate is great preparation for the expanding service. There is still a lot to do, including launching the Cybercab on time.
Tesla got its largest order for the all-electric Class 8 Semi yet, a 500-unit order from Einride AB, a Swedish trucking company.
Einride made the announcement this morning following its second-quarter earnings call. The company said it plans to use 500 Tesla Semi units on its fleet intelligence platform, called Saga AI. The deployments will serve large companies like Amazon and will extend Einride’s electric freight network across logistics routes in California, New Jersey, Texas, Illinois, and Georgia.
🚨 Tesla has received a MASSIVE order from Swedish freight company Einride AB, which placed an order for 500 Tesla Semi trucks
Tesla’s biggest order for the Semi yet! pic.twitter.com/PrtLp5yzvh
— TESLARATI (@Teslarati) August 18, 2026
The deployment is being carried out in several phases over the next two years as Tesla ramps production of the Semi at its dedicated production facility in Sparks, Nevada. Einride will receive its first Semi units in September.
Saga AI
Saga AI is Einride’s dedicated fleet intelligence platform. It enables scaled adoption of electric trucks for freight use and allows shippers to integrate electric capacity without the operational burden or capital risks of managing a fleet. This helps integrate cost-efficient logistics and makes budgeting and forecasting much more accurate.
Tesla Semi’s Adoption
The Tesla Semi is now gathering large-scale clients past those who have helped the company operate a Pilot Program to gain initial information and feedback from real-world drivers.
Perhaps the biggest and most notable is that of Frito-Lay and PepsiCo., who have worked with Tesla for the past several years to dial in the finer details of the truck, including its efficiency and operation-related components.
Tesla Semi gets strange-but-understandable comparison from Jay Leno
There has been tremendous progress in that time, and it even catalyzed Tesla to make some design changes, which were unveiled earlier this year.
But Einride CEO Roozbeh Charli says his company’s partnership with Tesla will continue to push those things forward:
“This deployment is yet another proof point that we can execute at the scale our customers demand. Working closely with Tesla to bring next-generation Semis into active operations quickly and at scale is a testament to the strength of that partnership, and how quickly this technology is maturing from promise to daily operations.”
Additionally, Dan Priestley, the Director of the Semi Program at Tesla, said the partnership is ideal due to Einride’s focus on sustainable transport:
“Einride is at the forefront of sustainable freight, and we are thrilled to deepen our relationship with them through this order of 500 Semis. EV heavy trucks provide lower costs per mile from fuel savings, reduced maintenance, and better uptime over diesel trucks. These savings increase further through operational efficiency when deploying EV trucks at scale, and we are excited that Einride recognizes this and look forward to supporting their deployments.”
Elon Musk
India tells Elon Musk’s X to “Follow the Law” in latest censorship update
Elon Musk says X now exposes government censorship, but India’s secrecy laws complicate that promise.
Elon Musk’s promise to make government censorship requests on X “clearly visible” is running into a wall in India, where the law forbids the very disclosure Musk is promising.
On August 15, Musk responded to an update from X’s open-source algorithm team by writing “Any censorship required by governments is now clearly visible.” The claim referred to a change X pushed two days earlier to its public xai-org/x-algorithm repository, which now includes a controversial filter written directly into the code. The filter suppresses posts from 665 accounts flagged by Brazil’s Superior Electoral Court from appearing in the For You feed of any viewer located in Brazil, unless the viewer already follows the account. The election tied to the filter is scheduled for October 4.
India’s government wasn’t as impressed, and responded on Monday that “X will have to follow the law of the land,” in response to Musk’s transparency push covered by the Times of India. The problem is structural rather than political. India issues content blocking orders under Section 69A of its IT Act, and Rule 16 of the accompanying 2009 Blocking Rules requires those orders to stay confidential. Publishing an India equivalent of the Brazil filter, naming specific accounts and citing specific government orders, would itself violate Indian law. Government use of Section 69A has grown from roughly 6,000 orders a year between 2018 and 2023 to about 24,300 in 2025, according to a Tech Times report.
The contrast puts Musk’s transparency pledge in an odd spot. It works largely as advertised in Brazil, where electoral law requires disclosure and X can point to specific account IDs and a specific court order in public code. It cannot work the same way in India, where the law requires the opposite. X users in India will keep seeing content disappear from search and their feeds without any public accounting of why, even as X tells the rest of the world that its censorship compliance is now inspectable.
This isn’t the first time X’s fights with a national government have shaped how the platform operates. Brazil’s Supreme Court ordered X to suspend the accounts of sitting lawmakers and journalists in 2024, a standoff that cost X its Brazilian revenue for months and froze Starlink’s local accounts before the investigation into Musk and X was closed in March with no evidence of wrongdoing found. X also sued California over a state law requiring moderation disclosures, arguing the mandate itself violated the First Amendment.
Whether India’s government pursues anything beyond a public statement remains to be seen. For now, the mismatch between what X can legally publish and what different governments legally allow it to publish is the real story behind Musk’s seven word claim.
Tesla reveals plans for Robotaxi charging hub in Austin
Tesla Semi gets its largest order yet
