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Tesla FSD Beta V11.3 starts shipping to employees (Release Notes)

Credit: Drive in EV/Twitter

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The release notes for Tesla FSD Beta V11.3 have been shared online. Observers from the electric vehicle community suggest that Tesla Full Self-Driving Beta 11.3 is rolling out to the company’s employee FSD Beta testers, at least for now. 

The following are Tesla’s FSD Beta V11.3 release notes

  • Enabled FSD Beta on highway. This unifies the vision and planning stack on and off-highway and replaces the legacy highway stack, which is over four years old. The legacy highway stack still relies on several single-camera and single-frame networks, and was setup to handle simple lane-specific maneuvers. FSD Beta’s multi-camera video networks and next-gen planner, that allows for more complex agent interactions with less reliance on lanes, make way for adding more intelligent behaviors, smoother control and better decision making.
  • Added voice drive-notes. After an intervention, you can now send Tesla an anonymous voice message describing your experience to help improve Autopilot.
  • Expanded Automatic Emergency Braking (AEB) to handle vehicles that cross ego’s path. This includes cases where other vehicles run their red light or turn across ego’s path, stealing the right-of-way.
  • Replay of previous collisions of this type suggests that 49% of the events would be mitigated by the new behavior. This improvement is now active in both manual driving and autopilot operation.
  • Improved autopilot reaction time to red light runners and stop sign runners by 500ms, by increased reliance on object’s instantaneous kinematics along with trajectory estimates.
  • Added a long-range highway lanes network to enable earlier response to blocked lanes and high curvature.
  • Reduced goal pose prediction error for candidate trajectory neural network by 40% and reduced runtime by 3X. This was achieved by improving the dataset using heavier and more robust offline optimization, increasing the size of this improved dataset by 4X, and implementing a better architecture and feature space.
  • Improved occupancy network detections by oversampling on 180K challenging videos including rain reflections, road debris, and high curvature.
  • Improved recall for close-by cut-in cases by 20% by adding 40k autolabeled fleet clips of this scenario to the dataset. Also improved handling of cut-in cases by improved modeling of their motion into ego’s lane, leveraging the same for smoother lateral and longitudinal control for cut-in objects.
  • Added “lane guidance module and perceptual loss to the Road Edges and Lines network, improving the absolute recall of lines by 6% and the absolute recall of road edges by 7%.
  • Improved overall geometry and stability of lane predictions by updating the “lane guidance” module representation with information relevant to predicting crossing and oncoming lanes.
  • Improved handling through high speed and high curvature scenarios by offsetting towards inner lane lines. 
  • Improved lane changes, including: earlier detection and handling for simultaneous lane changes, better gap selection when approaching deadlines, better integration between speed-based and nav-based lane change decisions and more differentiation between the FSD driving profiles with respect to speed lane changes.
  • Improved longitudinal control response smoothness when following lead vehicles by better modeling the possible effect of lead vehicles’ brake lights on their future speed profiles.
  • Improved detection of rare objects by 18% and reduced the depth error to large trucks by 9%, primarily from migrating to more densely supervised autolabeled datasets.
  • Improved semantic detections for school busses by 12% and vehicles transitioning from stationary-to-driving by 15%. This was achieved by improving dataset label accuracy and increasing dataset size by 5%.
  • Improved decision making at crosswalks by leveraging neural network based ego trajectory estimation in place of approximated kinematic models.
  • Improved reliability and smoothness of merge control, by deprecating legacy merge region tasks in favor of merge topologies derived from vector lanes.
  • Unlocked longer fleet telemetry clips (by up to 26%) by balancing compressed IPC buffers and optimized write scheduling across twin SOCs.

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Several longtime FSD Beta testers have pointed out some key improvements that would likely be very appreciated by users in V11.3. These include the systems’ improved handling through high speed and high curvature scenarios, as well as improvements to Automatic Emergency Braking (AEB). With the improvements in place, FSD Beta V11.3 would behave closer to a proper human driver. 

Comments from longtime Tesla FSD Beta testers also suggest that V11.3 is still only being released for company employees for now. Considering Tesla’s past updates, it would not be surprising if the greater FSD Beta fleet gets the V11.3 update in the coming week or so. This is, of course, unless V11.3 ends up going the way of FSD Beta V11, which was released to employees in November but not to the greater fleet of FSD Beta testers. 

The Teslarati team would appreciate hearing from you. If you have any tips, contact me at maria@teslarati.com or via Twitter @Writer_01001101.

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Maria--aka "M"-- is an experienced writer and book editor. She's written about several topics including health, tech, and politics. As a book editor, she's worked with authors who write Sci-Fi, Romance, and Dark Fantasy. M loves hearing from TESLARATI readers. If you have any tips or article ideas, contact her at maria@teslarati.com or via X, @Writer_01001101.

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Tesla expands massive safety feature worldwide in latest update

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Credit: Tesla

Tesla has expanded the footprint of a massive safety feature worldwide with a recent Software Update labeled as 2026.20.6. The expansion of the “Blind Spot Warning While Parked” feature represents the more widespread availability of the feature, which aims to prevent “dooring.”

Dooring is when a driver or passenger opens a car door into the path of an oncoming road user, usually a cyclist or motorcyclist. It is among the most common types of cycling accidents, the League of American Bicyclists says.

For this reason, Tesla created a feature that warns occupants not to open the door because an object is approaching. The feature will sound a chime, and it will also delay the opening of the door to prevent an incident.

The release notes state (via Not a Tesla App):

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“If you attempt to open a door while an approaching object is detected in your blind spot (for example, a bicyclist approaching from behind) a chime sounds, and your door will not open upon initial button press. Wait a short time and press the button a second time to override the warning.”

Tesla initially rolled out this feature back in 2024 with the Model 3 “Highland.” However, it remained with the Model 3 exclusively for over a year; that was until Tesla added it to the Cybertruck this past Spring.

Now, it is making its way to the new Model Y, 2021 and newer Model S, and 2021 or newer Model X.

The prevention of dooring incidents could eliminate many injuries to cyclists, especially in an urban setting. Dooring accounts for 10-20 percent of bike-related crashes in major cities, and over 17,000 dooring-related incidents were treated in the U.S. over the course of a decade. These usually involve fractures, contusions, and head trauma.

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Tesla sends production Cybercab with no steering wheel, pedals to on-road testing

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Credit: Tesla

Tesla confirmed this morning that it has sent the first production units, manufactured with no steering wheel or pedals, to on-road testing in Austin, sharing video of the first rides with no human controls.

The lack of steering wheels and pedals in the Cybercab aligns with Tesla’s self-certification of Robotaxi as Level 4 SAE, a platform it plans to make widespread through internal vehicles and customer-owned cars that will operate and generate revenue for individuals.

The start of these engineering tests is a major signal for Tesla, which plans to bring driverless, wheel-less, and pedal-less Cybercabs to market in the coming months. With production already well underway at Gigafactory Texas, where the Cybercab is built, there is some inclination to believe the first public rides could happen sooner rather than later.

Tesla’s engineering tests will put the Cybercab in real-world scenarios, testing not only the hardware, but more importantly, the software that drives the car around Austin with nobody supervising it within the car.

This is perhaps the biggest part of the internal testing process, especially prior to allowing regular, everyday people to hail the Cybercab for an autonomous ride. These early rides serve as a true benchmark for Tesla: How many rides can it achieve safely? How many miles did it travel consecutively without needing an intervention? What scenarios challenge the Full Self-Driving suite the most?

The proper precautions have already been put into place as well, as Tesla released the First Responders Guide to Cybercab over the weekend, ensuring that emergency services have 24/7 access to Robotaxi Assistance, as well as other boundaries, such as Geofencing features that can be used to redirect autonomous vehicle traffic due to accidents, road closures, construction, or maintenance.

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Cybercab seems genuinely close to being added to the Robotaxi fleet in Austin, but Tesla has prioritized safety throughout this entire process. Therefore, we think it could be months before it truly starts giving rides to the public. People have been frustrated with this, but Robotaxi in Austin has a tremendous safety record so far, so the slow rollout has kept people safe and accidents to a minimum.

The most important thing is that Tesla continues to show consistent progress in the Cybercab’s ramp-up toward fleet addition. A few weeks back, we saw the EPA reward the Cybercab a Certificate of Conformity, allowing it to enter the stream of commerce. Then, we saw Tesla add decals, signaling that it was likely about to start testing it publicly. That has now happened.

The next big move will be the announcement of the first rides, so this Summer should be filled with anticipation.

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Elon Musk

Tesla Phone? Not quite, but close: analyst

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elon musk phone
Photo: Boss Hunting.com.au

For years, there have been images and videos across social media platforms that have reminded me of when I was a 15-year-old kid teased by “Xbox 720” videos on YouTube. These videos are of the supposed “Tesla Phone” that Elon Musk was secretly developing in between leading Tesla with its electric cars and SpaceX with its reusable rockets.

Although Musk has put those rumors to bed several times, it was never completely out of the realm that he could get involved in cell phones in some capacity. Think outside the box and more macro-level, though. Instead of reinventing the computer, Musk reinvented connectivity by developing Starlink with SpaceX.

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It could be something similar, TD Cowen analyst Gregory Williams said in a note last week, where he hinted SpaceX could be gathering some steam to acquire T-Mobile.

Williams said it would be the “clear choice” for SpaceX if it decided to go through with a network acquisition. He also suggested AT&T.

The move would be possible through selling more of its own stock, which would help SpaceX raise the money to purchase T-Mobile, which would cost roughly $300 billion. It could be one of the moves SpaceX makes post-IPO in terms of an acquisition: it already acquired Cursor AI for $60 billion.

Other analysts, like Dan Ives of Wedbush, believe SpaceX and Tesla will eventually merge into one anyway, and that conglomeration could come as soon as this year, some have said.

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The implications of SpaceX purchasing T-Mobile are massive. A combined entity would create a truly ubiquitous network: T-Mobile’s terrestrial 5G towers and Starlink’s growing constellation of Direct-to-Cell satellites. This would essentially eliminate dead zones across the U.S. and potentially globally.

SpaceX would instantly become a full-scale facilities-based carrier with satellite differentiation; a huge advantage. This would pressure AT&T and Verizon heavily.

There are also concerns like a potential reduction in long-term competition, and of course, a deal of that size would face intense scrutiny from government agencies.

The strategic fit is compelling due to the existing Starlink–T-Mobile partnership and complementary technologies (space + terrestrial). It could create a dominant integrated communications player. However, the regulatory, financial, and execution hurdles are enormous — this remains highly speculative with no indication SpaceX is actively pursuing it right now.

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