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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 officially opened Robotaxi access to everyone and everyone, but there is one catch: you have to have an iPhone.
Tesla’s Robotaxi service in Austin and its ride-hailing service in the Bay Area were both officially launched to the public today, giving anyone using the iOS platform the ability to simply download the app and utilize it for a ride in either of those locations.
It has been in operation for several months: it launched in Austin in late June and in the Bay Area about a month later. In Austin, there is nobody in the driver’s seat unless the route takes you on the freeway.
In the Bay Area, there is someone in the driver’s seat at all times.
The platform was initially launched to those who were specifically invited to Austin to try it out.
Tesla confirms Robotaxi is heading to five new cities in the U.S.
Slowly, Tesla launched the platform to more people, hoping to expand the number of rides and get more valuable data on its performance in both regions to help local regulatory agencies relax some of the constraints that were placed on it.
Additionally, Tesla had its own in-house restrictions, like the presence of Safety Monitors in the vehicles. However, CEO Elon Musk has maintained that these monitors were present for safety reasons specifically, but revealed the plan was to remove them by the end of the year.
Now, Tesla is opening up Robotaxi to anyone who wants to try it, as many people reported today that they were able to access the app and immediately fetch a ride if they were in the area.
We also confirmed it ourselves, as it was shown that we could grab a ride in the Bay Area if we wanted to:
🚨 Tesla Robotaxi ride-hailing Service in Austin and the Bay Area has opened up for anyone on iOS
Go download the app and, if you’re in the area, hail a ride from Robotaxi pic.twitter.com/1CgzG0xk1J
— TESLARATI (@Teslarati) November 18, 2025
The launch of a more public Robotaxi network that allows anyone to access it seems to be a serious move of confidence by Tesla, as it is no longer confining the service to influencers who are handpicked by the company.
In the coming weeks, we expect Tesla to then rid these vehicles of the Safety Monitors as Musk predicted. If it can come through on that by the end of the year, the six-month period where Tesla went from launching Robotaxi to enabling driverless rides is incredibly impressive.
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Tesla analyst sees Full Self-Driving adoption rates skyrocketing: here’s why
“You’ll see increased adoption as people are exposed to it. I’ve been behind the wheel of several of these and the different iterations of FSD, and it is getting better and better. It’s something when people experience it, they will be much more comfortable utilizing FSD and paying for it.”
Tesla analyst Stephen Gengaro of Stifel sees Full Self-Driving adoption rates skyrocketing, and he believes more and more people will commit to paying for the full suite or the subscription service after they try it.
Full Self-Driving is Tesla’s Level 2 advanced driver assistance suite (ADAS), and is one of the most robust on the market. Over time, the suite gets better as the company accumulates data from every mile driven by its fleet of vehicles, which has swelled to over five million cars sold.
The suite features a variety of advanced driving techniques that many others cannot do. It is not your typical Traffic-Aware Cruise Control (TACC) and Lane Keeping ADAS system. Instead, it can handle nearly every possible driving scenario out there.
It still requires the driver to pay attention and ultimately assume responsibility for the vehicle, but their hands are not required to be on the steering wheel.
It is overwhelmingly impressive, and as a personal user of the FSD suite on a daily basis, I have my complaints, but overall, there are very few things it does incorrectly.
Tesla Full Self-Driving (Supervised) v14.1.7 real-world drive and review
Gengaro, who increased his Tesla price target to $508 yesterday, said in an interview with CNBC that adoption rates of FSD will increase over the coming years as more people try it for themselves.
At first, it is tough to feel comfortable with your car literally driving you around. Then, it becomes second nature.
Gengaro said:
“You’ll see increased adoption as people are exposed to it. I’ve been behind the wheel of several of these and the different iterations of FSD, and it is getting better and better. It’s something when people experience it, they will be much more comfortable utilizing FSD and paying for it.”
Tesla Full Self-Driving take rates also have to increase as part of CEO Elon Musk’s recently approved compensation package, as one tranche requires ten million active subscriptions in order to win that portion of the package.
The company also said in the Q3 2025 Earnings Call in October that only 12 percent of the current ownership fleet are paid customers of Full Self-Driving, something the company wants to increase considerably moving forward.
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Tesla scores major court win as judge rejects race bias class action
The ruling means the 2017 lawsuit cannot proceed as a class action because plaintiff attorneys were unable to secure testimony commitments from at least 200 workers.
Tesla scored a significant legal victory in California after a state judge reversed a class certification in a high-profile race harassment case involving 6,000 Black workers at its Fremont plant. The ruling means the 2017 lawsuit cannot proceed as a class action because plaintiff attorneys were unable to secure testimony commitments from at least 200 workers ahead of a 2026 trial, a threshold the judge viewed as necessary to reliably represent the full group.
No class action
In a late-Friday order, California Superior Court Judge Peter Borkon concluded that the suit could not remain a class action, stating he could not confidently apply the experiences of a much smaller group of testifying workers to thousands of potential class members. His ruling reverses a 2024 decision by a different judge who had certified the case under the belief that a trial of that size would be manageable, as noted in a Reuters report.
The lawsuit was originally filed by former assembly-line worker Marcus Vaughn, who alleged that Black employees at Tesla’s Fremont factory were exposed to various forms of racially hostile conduct, including slurs, graffiti, and instances of disturbing objects appearing in work areas. Tesla has previously said it does not tolerate harassment and has removed employees found responsible for misconduct. Neither Tesla nor the plaintiffs’ legal team immediately commented on the latest ruling.
Tesla’s legal challenges
While the decertification narrows the scope of this particular case, Tesla still faces additional litigation over similar allegations. A separate trial involving related claims brought by a California state civil rights agency is scheduled just two months after the now-vacated class trial date. The company is also contending with federal race discrimination claims filed by the U.S. Equal Employment Opportunity Commission, alongside several individual lawsuits it has already resolved.
For now, the reversal removes the large-scale exposure Tesla would have faced in a unified class trial, shifting the dispute back to individual claims rather than a single mass action. The case is Vaughn v. Tesla, filed in Alameda County Superior Court.
Tesla opens Robotaxi access to everyone — but there’s one catch
Tesla analyst sees Full Self-Driving adoption rates skyrocketing: here’s why
