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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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Tesla Model Y and Model 3 named safest vehicles tested by ANCAP in 2025

According to ANCAP in a press release, the Tesla Model Y achieved the highest overall weighted score of any vehicle assessed in 2025.

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Credit: ANCAP

The Tesla Model Y recorded the highest overall safety score of any vehicle tested by ANCAP in 2025. The Tesla Model 3 also delivered strong results, reinforcing the automaker’s safety leadership in Australia and New Zealand.

According to ANCAP in a press release, the Tesla Model Y achieved the highest overall weighted score of any vehicle assessed in 2025. ANCAP’s 2025 tests evaluated vehicles across four key pillars: Adult Occupant Protection, Child Occupant Protection, Vulnerable Road User Protection, and Safety Assist technologies.

The Model Y posted consistently strong results in all four categories, distinguishing itself through a system-based safety approach that combines structural crash protection with advanced driver-assistance features such as autonomous emergency braking, lane support, and driver monitoring. 

This marked the second time the Model Y has topped ANCAP’s annual safety rankings. The Model Y’s previous version was also ANCAP’s top performer in 2022.

The Tesla Model 3 also delivered a strong performance in ANCAP’s 2025 tests, contributing to Tesla’s broader safety presence across segments. Similar to the Model Y, the Model 3 also earned impressive scores across the ANCAP’s four pillars. This made the vehicle the top performer in the Medium Car category.  

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ANCAP Chief Executive Officer Carla Hoorweg stated that the results highlight a growing industry shift toward integrated safety design, with improvements in technologies such as autonomous emergency braking and lane support translating into meaningful real-world protection.

“ANCAP’s testing continues to reinforce a clear message: the safest vehicles are those designed with safety as a system, not a checklist. The top performers this year delivered consistent results across physical crash protection, crash avoidance and vulnerable road user safety, rather than relying on strength in a single area.

“We are also seeing increasing alignment between ANCAP’s test requirements and the safety technologies that genuinely matter on Australian and New Zealand roads. Improvements in autonomous emergency braking, lane support, and driver monitoring systems are translating into more robust protection,” Hoorweg said.

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Tesla Sweden uses Megapack battery to bypass unions’ Supercharger blockade

Just before Christmas, Tesla went live with a new charging station in Arlandastad, outside Stockholm, by powering it with a Tesla Megapack battery.

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Credit: Tesla Charging/X

Tesla Sweden has successfully launched a new Supercharger station despite an ongoing blockade by Swedish unions, using on-site Megapack batteries instead of traditional grid connections. The workaround has allowed the Supercharger to operate without direct access to Sweden’s electricity network, which has been effectively frozen by labor action.

Tesla has experienced notable challenges connecting its new charging stations to Sweden’s power grid due to industrial action led by Seko, a major Swedish trade union, which has blocked all new electrical connections for new Superchargers. On paper, this made the opening of new Supercharger sites almost impossible.

Despite the blockade, Tesla has continued to bring stations online. In Malmö and Södertälje, new Supercharger locations opened after grid operators E.ON and Telge Nät activated the sites. The operators later stated that the connections had been made in error. 

More recently, however, Tesla adopted a different strategy altogether. Just before Christmas, Tesla went live with a new charging station in Arlandastad, outside Stockholm, by powering it with a Tesla Megapack battery, as noted in a Dagens Arbete (DA) report. 

Because the Supercharger station does not rely on a permanent grid connection, Tesla was able to bypass the blocked application process, as noted by Swedish car journalist and YouTuber Peter Esse. He noted that the Arlandastad Supercharger is likely dependent on nearby companies to recharge the batteries, likely through private arrangements.

Eight new charging stalls have been launched in the Arlandastad site so far, which is a fraction of the originally planned 40 chargers for the location. Still, the fact that Tesla Sweden was able to work around the unions’ efforts once more is impressive, especially since Superchargers are used even by non-Tesla EVs.

Esse noted that Tesla’s Megapack workaround is not as easily replicated in other locations. Arlandastad is unique because neighboring operators already have access to grid power, making it possible for Tesla to source electricity indirectly. Still, Esse noted that the unions’ blockades have not affected sales as much.

“Many want Tesla to lose sales due to the union blockades. But you have to remember that sales are falling from 2024, when Tesla sold a record number of cars in Sweden. That year, the unions also had blockades against Tesla. So for Tesla as a charging operator, it is devastating. But for Tesla as a car company, it does not matter in terms of sales volumes. People charge their cars where there is an opportunity, usually at home,” Esse noted. 

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Elon Musk

Elon Musk’s X goes down as users report major outage Friday morning

Error messages and stalled loading screens quickly spread across the service, while outage trackers recorded a sharp spike in user reports.

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Credit: Linda Yaccarino/X

Elon Musk’s X experienced an outage Friday morning, leaving large numbers of users unable to access the social media platform.

Error messages and stalled loading screens quickly spread across the service, while outage trackers recorded a sharp spike in user reports.

Downdetector reports

Users attempting to open X were met with messages such as “Something went wrong. Try reloading,” often followed by an endless spinning icon that prevented access, according to a report from Variety. Downdetector data showed that reports of problems surged rapidly throughout the morning.

As of 10:52 a.m. ET, more than 100,000 users had reported issues with X. The data indicated that 56% of complaints were tied to the mobile app, while 33% were related to the website and roughly 10% cited server connection problems. The disruption appeared to begin around 10:10 a.m. ET, briefly eased around 10:35 a.m., and then returned minutes later.

Credit: Downdetector

Previous disruptions

Friday’s outage was not an isolated incident. X has experienced multiple high-profile service interruptions over the past two years. In November, tens of thousands of users reported widespread errors, including “Internal server error / Error code 500” messages. Cloudflare-related error messages were also reported.

In March 2025, the platform endured several brief outages spanning roughly 45 minutes, with more than 21,000 reports in the U.S. and 10,800 in the U.K., according to Downdetector. Earlier disruptions included an outage in August 2024 and impairments to key platform features in July 2023.

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