Connect with us
tesla-fsd-beta-v-11-3-release-date tesla-fsd-beta-v-11-3-release-date

News

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

Credit: Drive in EV/Twitter

Published

on

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.

Advertisement

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.

Advertisement

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.

Advertisement
Comments

News

Tesla’s Apple CarPlay ambitions are not dead, they’re still in the works

For what it’s worth, as a Tesla owner, I don’t particularly see the need for CarPlay, as I have found the in-car system that the company has developed to be superior. However, many people are in love with CarPlay simply because, when it’s in a car that is capable, it is really great.

Published

on

Credit: Michał Gapiński/YouTube

Tesla’s Apple CarPlay ambitions appeared to be dead in the water after a large amount of speculation late last year that the company would add the user interface seemed to cool down after several weeks of reports.

However, it appears that CarPlay might make its way to Tesla vehicles after all, as a recent report seems to indicate that it is still being worked on by software teams for the company.

The real question is whether it is truly needed or if it is just a want by so many owners that Tesla is listening and deciding to proceed with its development.

Back in NovemberBloomberg reported that Tesla was in the process of testing Apple CarPlay within its vehicles, which was a major development considering the company had resisted adopting UIs outside of its own for many years.

Advertisement

Nearly one-third of car buyers considered the lack of CarPlay as a deal-breaker when buying their cars, a study from McKinsey & Co. outlined. This could be a driving decision in Tesla’s inability to abandon the development of CarPlay in its vehicles, especially as it lost a major advantage that appealed to consumers last year: the $7,500 EV tax credit.

Tesla owners propose interesting theory about Apple CarPlay and EV tax credit

Although we saw little to no movement on it since the November speculation, Tesla is now reportedly in the process of still developing the user interface. Mark Gurman, a Bloomberg writer with a weekly newsletter, stated that CarPlay is “still in the works” at Tesla and that more concrete information will be available “soon” regarding its development.

While Tesla already has a very capable and widely accepted user interface, CarPlay would still be an advantage, considering many people have used it in their vehicles for years. Just like smartphones, many people get comfortable with an operating system or style and are resistant to using a new one. This could be a big reason for Tesla attempting to get it in their own cars.

Advertisement

Tesla gets updated “Apple CarPlay” hack that can work on new models

For what it’s worth, as a Tesla owner, I don’t particularly see the need for CarPlay, as I have found the in-car system that the company has developed to be superior. However, many people are in love with CarPlay simply because, when it’s in a car that is capable, it is really great.

It holds one distinct advantage over Tesla’s UI in my opinion, and that’s the ability to read and respond to text messages, which is something that is available within a Tesla, but is not as user-friendly.

With that being said, I would still give CarPlay a shot in my Tesla. I didn’t particularly enjoy it in my Bronco Sport, but that was because Ford’s software was a bit laggy with it. If it were as smooth as Tesla’s UI, which I think it would be, it could be a really great addition to the vehicle.

Advertisement
Continue Reading

News

Tesla brings closure to Model Y moniker with launch of new trim level

Published

on

Credit: Tesla

With the launch of a new trim level for the Model Y last night, something almost went unnoticed — the loss of a moniker that Tesla just recently added to a couple of its variants of the all-electric crossover.

Tesla launched the Model Y All-Wheel-Drive last night, competitively priced at $41,990, but void of the luxurious features that are available within the Premium trims.

Upon examination of the car, one thing was missing, and it was noticeable: Tesla dropped the use of the “Standard” moniker to identify its entry-level offerings of the Model Y.

The Standard Model Y vehicles were introduced late last year, primarily to lower the entry price after the U.S. EV tax credit changes were made. Tesla stripped some features like the panoramic glass roof, premium audio, ambient lighting, acoustic-lined glass, and some of the storage.

Advertisement

Last night, it simply switched the configurations away from “Standard” and simply as the Model Y Rear-Wheel-Drive and Model Y All-Wheel-Drive.

There are three plausible reasons for this move, and while it is minor, there must be an answer for why Tesla chose to abandon the name, yet keep the “Premium” in its upper-level offerings.

“Standard” carried a negative connotation in marketing

Words like “Standard” can subtly imply “basic,” “bare-bones,” or “cheap” to consumers, especially when directly contrasted with “Premium” on the configurator or website. Dropping it avoids making the entry-level Model Y feel inferior or low-end, even though it’s designed for affordability.

Tesla likely wanted the base trim to sound neutral and spec-focused (e.g., just “RWD” highlights drivetrain rather than feature level), while “Premium” continues to signal desirable upgrades, encouraging upsells to higher-margin variants.

Advertisement

Simplifying the overall naming structure for less confusion

The initial “Standard vs. Premium” split (plus Performance) created a somewhat clunky hierarchy, especially as Tesla added more variants like Standard Long Range in some markets or the new AWD base.

Removing “Standard” streamlines things to a more straightforward progression (RWD → AWD → Premium RWD/AWD → Performance), making the lineup easier to understand at a glance. This aligns with Tesla’s history of iterative naming tweaks to reduce buyer hesitation.

Elevating brand perception and protecting perceived value

Keeping “Premium” reinforces that the bulk of the Model Y lineup (especially the popular Long Range models) remains a premium product with desirable features like better noise insulation, upgraded interiors, and tech.

Eliminating “Standard” prevents any dilution of the Tesla brand’s upscale image—particularly important in a competitive EV market—while the entry-level variants can quietly exist as accessible “RWD/AWD” options without drawing attention to them being decontented versions.

Advertisement

You can check out the differences between the “Standard” and “Premium” Model Y vehicles below:

@teslarati There are some BIG differences between the Tesla Model Y Standard and Tesla Model Y Premium #tesla #teslamodely ♬ Sia – Xeptemper

Continue Reading

Elon Musk

Tesla bull sees odds rising of Tesla merger after Musk confirms SpaceX-xAI deal

Dan Ives of Wedbush Securities wrote on Tuesday that there is a growing chance Tesla could be merged in some form with SpaceX and xAI over the next 12 to 18 months.

Published

on

Credit: Tesla China

A prominent Tesla (NASDAQ:TSLA) bull has stated that the odds are rising that Tesla could eventually merge with SpaceX and xAI, following Elon Musk’s confirmation that the private space company has combined with his artificial intelligence startup. 

Dan Ives of Wedbush Securities wrote on Tuesday that there is a growing chance Tesla could be merged in some form with SpaceX and xAI over the next 12 to 18 months.

“In our view there is a growing chance that Tesla will eventually be merged in some form into SpaceX/xAI over time. The view is this growing AI ecosystem will focus on Space and Earth together…..and Musk will look to combine forces,” Ives wrote in a post on X.

Ives’ comments followed confirmation from Elon Musk late Monday that SpaceX has merged with xAI. Musk stated that the merger creates a vertically integrated platform that combines AI, rockets, satellite internet, communications, and real-time data.

Advertisement

In a post on SpaceX’s official website, Elon Musk added that the combined company is aimed at enabling space-based AI compute, stating that within two to three years, space could become the lowest-cost environment for generating AI processing power. The transaction reportedly values the combined SpaceX-xAI entity at roughly $1.25 trillion.

Tesla, for its part, has already increased its exposure to xAI, announcing a $2 billion investment in the startup last week in its Q4 and FY 2025 update letter.

While merger speculation has intensified, notable complications could emerge if SpaceX/xAI does merge with Tesla, as noted in a report from Investors Business Daily.

SpaceX holds major U.S. government contracts, including with the Department of Defense and NASA, and xAI’s Grok is being used by the U.S. Department of War. Tesla, for its part, maintains extensive operations in China through Gigafactory Shanghai and its Megapack facility. 

Advertisement
Continue Reading