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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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Tesla expands Robotaxi in a way that was long anticipated
Instead, it has to do with the consumer base it offers Robotaxi to, because it has not offered it to everyone in the past.
Tesla has expanded Robotaxi in a way that was long anticipated, and it does not have to do with a new, larger geofence in a city where it already offered its partially autonomous ride-hailing suite, or a new city altogether.
Instead, it has to do with the consumer base it offers Robotaxi to, because it has not offered it to everyone in the past.
Tesla has taken a major step forward in its autonomous ride-hailing ambitions with the official launch of the Tesla Robotaxi app for Android users. Released on the Google Play Store on April 24. Titled simply “Tesla Robotaxi,” the app is now available to download directly from Tesla.
The @Tesla Robtoaxi App has just officially launched for Android users. Go get some rides y’all!
Download: https://t.co/D2jIONXc91 pic.twitter.com/rQ6TD14zkC
— Sawyer Merritt (@SawyerMerritt) April 24, 2026
This rollout fulfills a long-anticipated expansion that opens the service to hundreds of millions of Android smartphone users who were previously unable to access it on iOS alone.
The app delivers a streamlined, driverless ride experience powered by Tesla’s automated driving technology.
Users sign in with a Tesla Account, view the current service area map within the app, enter a destination, and receive an estimated fare and arrival time before confirming the ride. When a Model Y from the Robotaxi fleet arrives, riders confirm the license plate, enter the vehicle, fasten their seatbelt, and tap “Start Ride” on either the app or the vehicle’s touchscreen.
During the trip, passengers have access to all the same controls that iOS users do, and can adjust climate settings, seat positions, and music while tracking progress on an in-app map. The interface also allows drop-off changes or support requests if needed. After the ride, users exit, close the doors, and submit feedback.
This Android availability directly broadens the rider base for Robotaxi in its initial service areas. Unfortunately, Android users are used to being subject to delayed launches of new features available to Tesla owners.
By removing the iOS-only barrier, Tesla instantly expands the addressable market, enabling far more people to summon and use the autonomous vehicles already operating on public roads.
The move is a foundational requirement for scaling ride volume and gathering the real-world data needed to refine the unsupervised Full Self-Driving system that powers every trip.
For the Robotaxi program itself, the launch signals steady operational progress. It prepares the service for higher utilization rates as the fleet grows and supports the transition from limited early deployments to a more robust network.
Tesla expands Unsupervised Robotaxi service to two new cities
Tesla has indicated that users outside current service areas can sign up at the company’s website for future notifications, pointing to a deliberate, phased geographic rollout.
Looking ahead, the company plans to incorporate Cybercab vehicles to increase fleet capacity and efficiency while continuing to expand service territories. With the Android app now live, Tesla has removed a key adoption hurdle and positioned Robotaxi for the next phase of growth in autonomous urban transportation.
The infrastructure is now in place to support significantly larger rider demand as production and deployment accelerate.
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UPDATE: SpaceX’s Falcon Heavy that launched a Tesla into space is back on a mission
SpaceX Falcon Heavy returns after 18 months away to deliver a satellite that only it could carry.
UPDATE: 10:29 a.m. et: SpaceX is standing down from today’s Falcon Heavy launch of the ViaSat-3 F3 mission due to unfavorable weather. A new target date will be shared once confirmed.
After an 18-month absence, SpaceX’s Falcon Heavy is returning to mission on Monday morning when it’s scheduled to lift off from Launch Complex 39A at Kennedy Space Center at 10:21 a.m. EDT.
The mission is called ViaSat-3 F3, and the heavy satellite payload needs to reach geostationary orbit, sitting 22,236 miles above Earth where its speed matches the planet’s rotation. Getting a satellite that heavy to that altitude demands more thrust than a single-core Falcon 9 can deliver.
This marks the Falcon Heavy’s 12th flight overall since its debut in February 2018, and its first since NASA’s Europa Clipper mission in October 2024.
Arguably, the most exciting element for spectators will be watching the booster recoveries in action when the two side boosters, B1072 and B1075, will attempt simultaneous landings at Landing Zone 2 and the newer Landing Zone 40 at Cape Canaveral Space Force Station, while the center core will be expended over the ocean.
SpaceX wins its first MARS contract but it comes with a catch
Following satellite deployment, expected roughly five hours after launch, ViaSat-3 F3 will spend several months traveling to its final orbital slot before undergoing in-orbit testing, with service entry expected by late summer 2026
As Teslarati reported, NASA awarded SpaceX a $175.7 million contract on April 16, 2026, to launch the ESA Rosalind Franklin Mars rover aboard a Falcon Heavy no earlier than late 2028, which would mark the first time SpaceX has ever sent a payload to Mars. That contract came on top of an already deep pipeline that includes the Roman Space Telescope, the Dragonfly Saturn mission, and multiple national security payloads.
SpaceX executed 165 missions in 2025 and now accounts for approximately 85% of all global orbital launches. With Starlink surpassing 10 million subscribers and an IPO targeting a $1.75 trillion valuation still ahead, Monday’s launch is one more data point in a company that has quietly become the backbone of both commercial and government space access worldwide.
Tesla is launching its solution to end Supercharger fights once and for all, eliminating any confusion on who is to charge next at a congested location.
Last year, a notable incident at a Tesla Supercharger led to a fight, and it all stemmed from a disagreement over who arrived at the location first.
Congestion at Tesla Superchargers is a pretty infrequent occurrence for most of us, but there are more congested and popular areas where wait times can be extensive. An unfortunate growing pain of EV ownership is the plain fact that chargers are not as available as gas pumps, and there are, at times, lines to charge.
This can cause tensions to flare and people to get entitled when visiting Superchargers. Nobody wants to spend hours at a Supercharger, but now, there will be no more confusion when there is a queue, and that’s thanks to Tesla’s new Virtual Queue for Superchargers.
Tesla is finally starting to build out the Virtual Supercharger Queue, according to Not a Tesla App, but it still relies on drivers to make it work.
When a driver is near a Supercharger that is full, a message will pop up on the Tesla App, using the driver’s location to determine their eligibility to join the virtual queue.
The app states:
“While the app is closed, Tesla uses your location to notify you of accurate wait times at Superchargers when you arrive.”
Another message within the app states:
“There is a waitlist to charge. Are you sure you want to start a charging session now?”
This sounds as if it will require drivers to act appropriately and only plug in when the app prompts them to do so, by letting them know it is their turn.
The app will notify the driver of their position in the queue, as well as how many vehicles are ahead of them.
Tesla launches first ‘true’ East Coast V4 Supercharger: here’s what that means
The company announced a while back that it would be working on a solution for this issue. Personally, I’ve only had to wait at a Supercharger for a charge on one occasion, and there was a line of between 3 and 10 cars during this singular occurrence.
I’m out at the Lancaster, PA Supercharger and showed up with a queue of three vehicles.
It’s now up to five and there have been several issues with order of arrival and confusion about who is first.
Any update on Supercharger queue? @elonmusk @aelluswamy @r_jegaa
— TESLARATI (@Teslarati) January 31, 2026
There were no conflicts or arguments about who had arrived first, but there was some discussion between several drivers during my time there about who was to charge first. Throw a non-Tesla EV into the mix, one that can only charge at a pull-in spot, and that causes even more of a complication.
Tesla expands Robotaxi in a way that was long anticipated
UPDATE: SpaceX’s Falcon Heavy that launched a Tesla into space is back on a mission
