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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.

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. 

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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.

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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SpaceX Starship Version 3 booster crumples in early testing

Photos of the incident’s aftermath suggest that Booster 18 will likely be retired.

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Credit: SpaceX/X

SpaceX’s new Starship first-stage booster, Booster 18, suffered major damage early Friday during its first round of testing in Starbase, Texas, just one day after rolling out of the factory. 

Based on videos of the incident, the lower section of the rocket booster appeared to crumple during a pressurization test. Photos of the incident’s aftermath suggest that Booster 18 will likely be retired. 

Booster test failure

SpaceX began structural and propellant-system verification tests on Booster 18 Thursday night at the Massey’s Test Site, only a few miles from Starbase’s production facilities, as noted in an Ars Technica report. At 4:04 a.m. CT on Friday, a livestream from LabPadre Space captured the booster’s lower half experiencing a sudden destructive event around its liquid oxygen tank section. Post-incident images, shared on X by @StarshipGazer, showed notable deformation in the booster’s lower structure.

Neither SpaceX nor Elon Musk had commented as of Friday morning, but the vehicle’s condition suggests it is likely a complete loss. This is quite unfortunate, as Booster 18 is already part of the Starship V3 program, which includes design fixes and upgrades intended to improve reliability. While SpaceX maintains a rather rapid Starship production line in Starbase, Booster 18 was generally expected to validate the improvements implemented in the V3 program.

Tight deadlines

SpaceX needs Starship boosters and upper stages to begin demonstrating rapid reuse, tower catches, and early operational Starlink missions over the next two years. More critically, NASA’s Artemis program depends on an on-orbit refueling test in the second half of 2026, a requirement for the vehicle’s expected crewed lunar landing around 2028.

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While SpaceX is known for diagnosing failures quickly and returning to testing at unmatched speed, losing the newest-generation booster at the very start of its campaign highlights the immense challenge involved in scaling Starship into a reliable, high-cadence launch system. SpaceX, however, is known for getting things done quickly, so it would not be a surprise if the company manages to figure out what happened to Booster 18 in the near future.

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Tesla FSD (Supervised) is about to go on “widespread” release

In a comment last October, Elon Musk stated that FSD V14.2 is “for widespread use.”

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Tesla has begun rolling out Full Self-Driving (Supervised) V14.2, and with this, the wide release of the system could very well begin. 

The update introduces a new high-resolution vision encoder, expanded emergency-vehicle handling, smarter routing, new parking options, and more refined driving behavior, among other improvements.

FSD V14.2 improvements

FSD (Supervised) V14.2’s release notes highlight a fully upgraded neural-network vision encoder capable of reading higher-resolution features, giving the system improved awareness of emergency vehicles, road obstacles, and even human gestures. Tesla also expanded its emergency-vehicle protocols, adding controlled pull-overs and yielding behavior for police cars, fire trucks, and ambulances, among others.

A deeper integration of navigation and routing into the vision network now allows the system to respond to blocked roads or detours in real time. The update also enhances decision-making in several complex scenarios, including unprotected turns, lane changes, vehicle cut-ins, and interactions with school buses. All in all, these improvements should help FSD (Supervised) V14.2 perform in a very smooth and comfortable manner.

Elon Musk’s predicted wide release

The significance of V14.2 grows when paired with Elon Musk’s comments from October. While responding to FSD tester AI DRIVR, who praised V14.1.2 for fixing “95% of indecisive lane changes and braking” and who noted that it was time for FSD to go on wide release, Musk stated that “14.2 for widespread use.”

FSD V14 has so far received a substantial amount of positive reviews from Tesla owners, many of whom have stated that the system now drives better than some human drivers as it is confident, cautious, and considerate at the same time. With V14.2 now rolling out, it remains to be seen if the update also makes it to the company’s wide FSD fleet, which is still populated by a large number of HW3 vehicles. 

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Tesla FSD V14.2 starts rolling out to initial batch of vehicles

It would likely only be a matter of time before FSD V14.2 videos are posted and shared on social media.

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Credit: Grok Imagine

Tesla has begun pushing Full Self-Driving (Supervised) v14.2 to its initial batch of vehicles. The update was initially observed by Tesla owners and veteran FSD users on social media platform X on Friday.

So far, reports of the update have been shared by Model Y owners in California whose vehicles are equipped with the company’s AI4 hardware, though it would not be surprising if more Tesla owners across the country receive the update as well. 

Based on the release notes of the update, key improvements in FSD V14.2 include a revamped neural network for better detection of emergency vehicles, obstacles, and human gestures, as well as options to select arrival spots. 

It would likely only be a matter of time before FSD V14.2 videos are posted and shared on social media.

Following are the release notes of FSD (Supervised) V14.2, as shared on X by longtime FSD tester Whole Mars Catalog.

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Release Notes

2025.38.9.5

Currently Installed

FSD (Supervised) v14.2

Full Self-Driving (Supervised) v14.2 includes:

  • Upgraded the neural network vision encoder, leveraging higher resolution features to further improve scenarios like handling emergency vehicles, obstacles on the road, and human gestures.
  • Added Arrival Options for you to select where FSD should park: in a Parking Lot, on the Street, in a Driveway, in a Parking Garage, or at the Curbside.
  • Added handling to pull over or yield for emergency vehicles (e.g. police cars, fire trucks, ambulances.
  • Added navigation and routing into the vision-based neural network for real-time handling of blocked roads and detours.
  • Added additional Speed Profile to further customize driving style preference.
  • Improved handling for static and dynamic gates.
  • Improved offsetting for road debris (e.g. tires, tree branches, boxes).
  • Improve handling of several scenarios including: unprotected turns, lane changes, vehicle cut-ins, and school busses.
  • Improved FSD’s ability to manage system faults and improve scenarios like handling emergency vehicles, obstacles on the road, and human gestures.
  • Added Arrival Options for you to select where FSD should park: in a Parking Lot, on the Street, in a Driveway, in a Parking Garage, or at the Curbside.
  • Added handling to pull over or yield for emergency vehicles (e.g. police cars, fire trucks, ambulances).
  • Added navigation and routing into the vision-based neural network for real-time handling of blocked roads and detours.
  • Added additional Speed Profile to further customize driving style preference.
  • Improved handling for static and dynamic gates.
  • Improved offsetting for road debris (e.g. tires, tree branches, boxes).
  • Improve handling of several scenarios, including unprotected turns, lane changes, vehicle cut-ins, and school buses.
  • Improved FSD’s ability to manage system faults and recover smoothly from degraded operation for enhanced reliability.
  • Added alerting for residue build-up on interior windshield that may impact front camera visibility. If affected, visit Service for cleaning!

Upcoming Improvements:

  • Overall smoothness and sentience
  • Parking spot selection and parking quality
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