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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.
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Man credits Grok AI with saving his life after ER missed near-ruptured appendix
The AI flagged some of the man’s symptoms and urged him to return to the ER immediately and demand a CT scan.
A 49-year-old man has stated that xAI’s Grok ended up saving his life when the large language model identified a near-ruptured appendix that his first ER visit dismissed as acid reflux.
After being sent home from the ER, the man asked Grok to analyze his symptoms. The AI flagged some of the man’s symptoms and urged him to return immediately and demand a CT scan. The scan confirmed that something far worse than acid reflux was indeed going on.
Grok spotted what a doctor missed
In a post on Reddit, u/Tykjen noted that for 24 hours straight, he had a constant “razor-blade-level” abdominal pain that forced him into a fetal position. He had no fever or visible signs. He went to the ER, where a doctor pressed his soft belly, prescribed acid blockers, and sent him home.
The acid blockers didn’t work, and the man’s pain remained intense. He then decided to open a year-long chat he had with Grok and listed every detail that he was experiencing. The AI responded quickly. “Grok immediately flagged perforated ulcer or atypical appendicitis, told me the exact red-flag pattern I was describing, and basically said “go back right now and ask for a CT,” the man wrote in his post.
He copied Grok’s reasoning, returned to the ER, and insisted on the scan. The CT scan ultimately showed an inflamed appendix on the verge of rupture. Six hours later, the appendix was out. The man said the pain has completely vanished, and he woke up laughing under anesthesia. He was discharged the next day.
How a late-night conversation with Grok got me to demand the CT scan that saved my life from a ruptured appendix (December 2025)
byu/Tykjen ingrok
AI doctors could very well be welcomed
In the replies to his Reddit post, u/Tykjen further explained that he specifically avoided telling doctors that Grok, an AI, suggested he get a CT scan. “I did not tell them on the second visit that Grok recommended the CT scan. I had to lie. I told them my sister who’s a nurse told me to ask for the scan,” the man wrote.
One commenter noted that the use of AI in medicine will likely be welcomed, stating that “If AI could take doctors’ jobs one day, I will be happy. Doctors just don’t care anymore. It’s all a paycheck.” The Redditor replied with, “Sadly yes. That is what it felt like after the first visit. And the following night could have been my last.”
Elon Musk has been very optimistic about the potential of robots like Tesla Optimus in the medical field. Provided that they are able to achieve human-level articulation in their hands, and Tesla is able to bring down their cost through mass manufacturing, the era of AI-powered medical care could very well be closer than expected.
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Tesla expands Model 3 lineup in Europe with most affordable variant yet
The Model 3 Standard still delivers more than 300 miles of range, potentially making it an attractive option for budget-conscious buyers.
Tesla has introduced a lower-priced Model 3 variant in Europe, expanding the lineup just two months after the vehicle’s U.S. debut. The Model 3 Standard still delivers more than 300 miles (480 km) of range, potentially making it an attractive option for budget-conscious buyers.
Tesla’s pricing strategy
The Model 3 Standard arrives as Tesla contends with declining registrations in several countries across Europe, where sales have not fully offset shifting consumer preferences. Many buyers have turned to options such as Volkswagen’s ID.3 and BYD’s Atto 3, both of which have benefited from aggressive pricing.
By removing select premium finishes and features, Tesla positioned the new Model 3 Standard as an “ultra-low cost of ownership” option of its all-electric sedan. Pricing comes in at €37,970 in Germany, NOK 330,056 in Norway, and SEK 449,990 in Sweden, depending on market. This places the Model 3 Standard well below the “premium” Model 3 trim, which starts at €45,970 in Germany.
Deliveries for the Standard model are expected to begin in the first quarter of 2026, giving Tesla an entry-level foothold in a segment that’s increasingly defined by sub-€40,000 offerings.
Tesla’s affordable vehicle push
The low-cost Model 3 follows October’s launch of a similarly positioned Model Y variant, signaling a broader shift in Tesla’s product strategy. While CEO Elon Musk has moved the company toward AI-driven initiatives such as robotaxis and humanoid robots, lower-priced vehicles remain necessary to support the company’s revenue in the near term.
Reports have indicated that Tesla previously abandoned plans for an all-new $25,000 EV, with the company opting to create cheaper versions of existing platforms instead. Analysts have flagged possible cannibalization of higher-margin models, but the move aims to counter an influx of aggressively priced entrants from China and Europe, many of which sell below $30,000. With the new Model 3 Standard, Tesla is reinforcing its volume strategy in Europe’s increasingly competitive EV landscape.
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Tesla FSD (Supervised) stuns Germany’s biggest car magazine
FSD Supervised recognized construction zones, braked early for pedestrians, and yielded politely on narrow streets.
Tesla’s upcoming FSD Supervised system, set for a European debut pending regulatory approval, is showing notably refined behavior in real-world testing, including construction zones, pedestrian detection, and lane changes, as per a recent demonstration ride in Berlin.
While the system still required driver oversight, its smooth braking, steering, and decision-making illustrated how far Tesla’s driver-assistance technology has advanced ahead of a potential 2026 rollout.
FSD’s maturity in dense city driving
During the Berlin test ride with Auto Bild, Germany’s largest automotive publication, a Tesla Model 3 running FSD handled complex traffic with minimal intervention, autonomously managing braking, acceleration, steering, and overtaking up to 140 km/h. It recognized construction zones, braked early for pedestrians, and yielded politely on narrow streets.
Only one manual override was required when the system misread a converted one-way route, an example, Tesla stated, of the continuous learning baked into its vision-based architecture.
Robin Hornig of Auto Bild summed up his experience with FSD Supervised with a glowing review of the system. As per the reporter, FSD Supervised already exceeds humans with its all-around vision. “Tesla FSD Supervised sees more than I do. It doesn’t get distracted and never gets tired. I like to think I’m a good driver, but I can’t match this system’s all-around vision. It’s at its best when both work together: my experience and the Tesla’s constant attention,” the journalist wrote.
Tesla FSD in Europe
FSD Supervised is still a driver-assistance system rather than autonomous driving. Still, Auto Bild noted that Tesla’s 360-degree camera suite, constant monitoring, and high computing power mark a sizable leap from earlier iterations. Already active in the U.S., China, and several other regions, the system is currently navigating Europe’s approval pipeline. Tesla has applied for an exemption in the Netherlands, aiming to launch the feature through a free software update as early as February 2026.
What Tesla demonstrated in Berlin mirrors capabilities already common in China and the U.S., where rival automakers have rolled out hands-free or city-navigation systems. Europe, however, remains behind due to a stricter certification environment, though Tesla is currently hard at work pushing for FSD Supervised’s approval in several countries in the region.
Man credits Grok AI with saving his life after ER missed near-ruptured appendix
Tesla expands Model 3 lineup in Europe with most affordable variant yet
