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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.
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“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.
Elon Musk
Tesla FSD takes owner on a 20,000+ mile joy ride
Tesla owner David Moss just pushed his intervention free FSD streak past 20,000 miles total.
Tesla Model 3 owner David Moss has spent the better part of eight months turning his vehicle into a rolling stress test for Full Self-Driving, and this week he pushed his single, continuous FSD streak past 20,000 miles without a human intervening.
Moss, a Tacoma, Washington resident who sells LiDAR scanning equipment for a living, first drew wide attention in December 2025 when he logged 10,000 consecutive miles on FSD v14.2. Days later he drove from the Tesla Diner in Los Angeles to Myrtle Beach, South Carolina, covering 2,732 miles in two days and 20 hours with zero disengagements, the first verified coast to coast autonomous drive in Tesla’s history. Tesla even featured the trip as an official customer story in March. That original streak eventually reached 12,961 miles across 30 states before ending in rural Wisconsin in January, when snow and single digit temperatures forced Moss to take over.
Tesla FSD successfully completes full coast-to-coast drive with zero interventions
He started over, and this run has gone further. In late May, Moss drove 3,760 miles across Canada with two companions, from Horseshoe Bay in Vancouver to a Tesla showroom in Halifax, again without a single intervention, a trip Tesla AI software VP Ashok Elluswamy publicly congratulated him for on X. In June, he pushed the same unbroken streak south, aiming to link the Canadian border to the Mexican border, and crossed 10,000 miles on Tesla’s newly added in car streak counter along the way, the first driver to do so since Tesla began showing confetti animations for the feature.
20,000 Mile Tesla FSD Screen Streak!
Special thank you to @DevinOlsenn, @scotsrule08, & @OwenSparks for helping co drive during all these fun adventures these last couple of months
Also thank you to @wholemars for always tracking me along the journey verifying it all with his… pic.twitter.com/CZ2yO6Ev0X
— David Moss (@DavidMoss) July 27, 2026
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It’s worth noting that every mile is logged through the FSD Database, a community run tracker built by Tesla influencer Omar Qazi, well known as @WholeMars on X, that pulls telemetry straight from the car and records disengagements down to a tenth of a mile. That verification is what separates Moss’s numbers from casual claims on social media.
The streak itself is a fairly recent addition to Tesla’s software. FSD v14.2 introduced a Self Driving Stats panel tracking the ratio of autonomous to manual miles, and v14.3.4 added the live streak counter in June, which resets the moment a driver brakes, wrenches the wheel or cancels navigation. Reaching 20,000 miles on that counter means a single Tesla drove itself through countless highways, city grids, construction zones and Supercharger stalls without a single reset.
Moss has said the goal was never to set a record for its own sake, but to show, mile by verified mile, what the software can already do.
Elon Musk told The Economist that artificial intelligence will likely surpass the combined intelligence of every human on Earth within about five years, and that humans may not remain in charge once that happens. In a wide-ranging interview with editor-in-chief Zanny Minton Beddoes, recorded at Giga Texas for the outlet’s Insider series, Musk compared the widening gap between AI and human intelligence to the gap between humans and chimpanzees.
“It’s hard to imagine that the chimpanzee would be in charge,” he said, addressing what happens to human authority once AI moves far beyond us.
Elon Musk reiterates his most optimistic prediction yet with “UHI” forecast
Musk’s timeline stretches out from there. Five years for AI to out-think humanity combined, ten years before humans lose meaningful control, and by 2036, he says, money itself may stop mattering.
Musk notes that if robots and AI produce more goods and services than people could ever consume, currency loses its purpose. He told Beddoes that governments could respond with direct payments, what he called “universal high income,” a term he first used in an X post last August describing a future where “everyone will have the best medical care, food, home, transport and everything else.”
There will be universal high income (not merely basic income).
Everyone will have the best medical care, food, home, transport and everything else.
Sustainable abundance.
-— Elon Musk (@elonmusk) August 24, 2025
He also floated a more surprising prediction that deflation, and not inflation, would become the bigger economic problem, since expanding the supply of goods and services faster than the money supply grows would push prices down rather than up.
None of this is new territory for Musk, who has spent years describing an “age of abundance” built on Optimus and autonomous vehicles. What’s notable is the timing. The interview landed the same week Tesla shares dropped roughly 19 percent following a second quarter earnings report that beat on revenue but missed badly on profit, and as SpaceX stock continues to slide from its post-IPO peak.
Musk’s own net worth has fallen close to $700 billion since mid-June, according to the Bloomberg Billionaires Index, even as he describes a future where personal wealth stops being the point.
Musk did not dodge the risk side of the equation either. He put the odds of AI contributing to human extinction somewhere in the 10 to 20 percent range, then arrived at what he called his “philosophical conclusion” since the technology cannot realistically be stopped and the arguably better response is to keep building it and hope the outcome leans toward abundance rather than catastrophe. “I’ve gone from exhilaration to terror regarding AI,” he told Beddoes, “even intraday.”
Tesla is adding a new “Traction Control Modes” feature to its cars for better handling in any conditions. These features will roll out to the Model 3 and Model Y, the two vehicles in Tesla’s lineup that typically do not have drive modes for various conditions.
Tesla did include this in the Model S and Model X, as well as the Cybertruck.
The new feature will roll out with the 2026 Summer Update, which Tesla announced last week and subsequently started rolling out to some owners today. The Summer Update is the latest iteration of the usual four seasonal releases the company rolls out throughout the year. These releases typically feature some owner-requested features, as well as improvements to things like the Full Self-Driving suite.
Tesla reveals 2026 Summer Update with crazy fixes to Nav and more
This release is no different. Among the changes are improvements to Navigation, new customization options with wraps and how they can be shared and stored, more functionality with the Tesla smartphone app, and new gamification with self-driving.
However, Tesla announced today that it was adding another feature to the Summer Update. Traction Control Modes will now be available with the release
Tesla describes them:
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“Choose from three updated Traction Control Modes: Auto for normal driving conditions, Slippery Surface for icy or wet roads, Stuck Assist when stuck in snow, mud, or sand. The mode resets to Auto at the start of each drive. To select, go to Controls > Dynamics > Traction Control Mode.”
Tesla’s 2026 Summer Update also includes new Traction Control Modes
📸: @PatchesHQ https://t.co/N9cD2lGP14 pic.twitter.com/ogLC5ROIgc
— TESLARATI (@Teslarati) July 26, 2026
The use of these modes will help improve a Tesla’s overall performance in less-than-ideal conditions. Typically, these traction control modes monitor wheel speed through sensors and track engine power to adjust responsiveness in various conditions.
These drive modes are not an ultimate solution to all driving conditions; just because there is a “Stuck Assist,” doesn’t mean your Tesla will dig itself out of a foot-and-a-half trench during a blizzard. It is important to remember that some of these scenarios also require some assistance from the driver. For example, driving in sand requires tires to be aired down significantly to increase traction and control.
However, this will be a welcome addition for those who use the Full Self-Driving suite and might not be convinced of its performance in adverse conditions. Some of us prefer to be in control in rain, snow, or ice, which is totally understandable. However, adjusting the Traction Control Mode while utilizing FSD in snow, rain, or ice could increase confidence and overall experience.
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Tesla’s Summer Update is already rolling out to some owners, so it should be making its way to most of the fleet over the next several weeks. The Spring Update rolled out at a very conservative pace, so if you don’t have it by the end of August, don’t be too upset. It might just be Tesla’s method.
Tesla FSD takes owner on a 20,000+ mile joy ride
Elon Musk explains what happens when AI outsmarts all of us
