Tesla FSD Beta 11.4.8 Release Notes Explained: Faster Decision Making, Improved Park Assist and More

A user on Reddit leaked the release notes for Tesla's next FSD Beta release

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Tesla's most recent FSD Beta, v11.4.7.3 was released almost a month ago on October 19th, but it now looks like Tesla may be looking to release another FSD Beta update.

Release notes for an alleged subsequent version, FSD Beta 11.4.8, have surfaced on Reddit. While their authenticity isn't confirmed, the release notes use the same syntax and language Tesla typically uses. Here's a breakdown of what may be included in Tesla's next FSD release.

Update: These release notes have now been confirmed and the update is rolling out to Tesla employees for further testing. The update is version 2023.27.11.

Simplified Autopilot Activation

Single-Tap Autopilot: The update reportedly allows drivers to activate Autopilot with just one press of the stalk, instead of the current two-press method. This could make engaging and disengaging Autopilot quicker and more straightforward.

This feature, along with separate audio for passengers using the rear display recently made its way to production in update 2023.38.8, which adds some credibility to these leaked release notes. This could also mean that this version of FSD Beta may be based on a more recent production branch, instead of the current version of 2023.27, which is now starting to lag in terms of features.

Advanced Video Processing

New Video Module: A new video processing component has been introduced to improve vehicle detection, movement understanding (semantics), speed (velocity), and other attributes. This improvement means the system can process visual information more efficiently and quickly, enhancing overall performance.

Enhanced Object Detection

Better Object Detection: The system's ability to notice objects crossing its path is said to be improved by 6%. Additionally, vehicle detection has become more precise due to updated data and the new video module.

Improved Vehicle Interaction

Cut-In Vehicle Detection: The precision in detecting vehicles that cut into the Tesla's lane is reportedly improved by 15%. This is crucial for safer lane changes and merges.

Accuracy in Speed and Movement

Reduced Errors in Speed and Acceleration: The system now makes fewer errors in judging other vehicles' speed (by 3%) and acceleration (by 10%). This means a more accurate response in traffic.

Faster Decision-Making

Reduced Network Latency: The update claims to reduce the delay (latency) in the vehicle's decision-making network by 15%, allowing for quicker responses without compromising performance.

Pedestrian and Cyclist Safety

Rotation Error Reduction: There's an over 8% reduction in errors related to understanding how pedestrians and cyclists are moving or turning. This could improve interactions with these road users.

Enhanced Parking Assistance

Vision Park Assist Accuracy: The geometric accuracy of the Vision Park Assist system is improved by 16%, making parking assistance more reliable by leveraging data from hardware 4 vehicles. It appears that these improvements will apply to all vehicles without ultrasonic sensors, although it's not very clear.

Smoother Lane Changes

Lane Change Accuracy: The accuracy of lane changes in response to path blockages is improved by 10%, likely leading to smoother and safer driving in complex traffic situations.

While these updates, if true, indicate a continued effort by Tesla to refine and improve FSD Beta, Tesla also continues work on the next major release of FSD Beta, version 12. V12 is expected to be 'end-to-end' neural networks, which will be the first time that neural networks are used to control the vehicle.

It's not clear when Tesla expects to release FSD v12, which is also when Musk says FSD will graduate from its beta status. Musk recently showed off FSD v12 and its capabilities in a livestream on X.

The complete release notes that were shared on Reddit are below.

FSD Beta 11.4.8 Release Notes

-Added option to activate Autopilot with a single stalk depression, instead of two, to help simplify activation and disengagement.

-Introduced a new efficient video module to the vehicle detection, semantics, velocity, and attributes networks that allowed for increased performance at lower latency.This was achieved by creating a multi-layered, hierarchical video module that caches intermediate computations to dramatically reduce the amount of compute that happens at any particular time.

-Improved distant crossing object detections by an additional 6%, and improved the precision of vehicle detection by refreshing old datasets with better autolabeling and introducing the new video module.

-Improved the precision of cut-in vehicle detection by 15%, with additional data and the changes to the video architecture that improve performance and latency.

-Reduced vehicle velocity error by 3%, and reduced vehicle acceleration error by 10%, by improving autolabeled datasets, introducing the new video module, and aligning model training and inference more closely.

-Reduced the latency of the vehicle semantics network by 15% with the new video module architecture, at no cost to performance.

-Reduced the error of pedestrian and bicycle rotation by over 8% by leveraging object kinematics more extensively when jointly optimizing pedestrian and bicycle tracks in autolabeled datasets.

-Improved geometric accuracy of Vision Park Assist predictions by 16%, by leveraging 10x more HW4 data, tripling resolution, and increasing overall stability of measurements.

-Improved path blockage lane change accuracy by 10% due to updates to static object detection networks.

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A Look at the Tesla Cybertruck’s Crumple Zones [VIDEO]

Not a Tesla App

Tesla’s Cybertruck has officially earned a 5-Star Safety Rating from the NHTSA—an impressive achievement given the vehicle’s design. The achievement demonstrates Tesla’s engineering prowess. As one engineer points out, it wasn’t an easy feat.

Interestingly, the NHTSA only recently disclosed the results, despite the crash tests being completed a while ago. According to Lars Moravy, Tesla’s VP of Vehicle Engineering, the team had been aware of the 5-star rating for quite some time. While the reason for the delay remains unclear, now that the results are public, Tesla’s engineers can finally share how they achieved the rating.

Crumple Zones

Wes Morril, the Cybertruck’s Lead Engineer, wrote about the crash test video on X recently, addressing the claims that the Cybertruck doesn’t have a crumple zone. He also posted a side-by-side video (below) of the engineering analysis and the crash test itself.

Engineered Crash Safety

There’s a lot of engineering precision at play when a Cybertruck is involved in a crash. Unlike traditional crash structures that rely on crash cans and collapse points, the Cybertruck’s front gigacasting is designed to absorb and redirect impact forces in a highly controlled manner.

It all starts with the bumper beam, which crushes within the first few milliseconds of a high-speed impact. At the same time, the vehicle’s sensors rapidly analyze the crash dynamics and determine the optimal deployment of safety restraints, including airbags and seat belt pre-tensioners. These split-second actions are crucial in keeping occupants safe.

As the crash progresses, the vehicle’s structure deforms in a carefully engineered sequence. The drive unit cradle bends, directing the solid drive unit downward and out of the way, allowing the gigacasting to begin absorbing impact forces.

The casting crushes cell by cell, methodically dissipating energy in a controlled manner. This gradual deceleration reduces the g-forces transferred to occupants, making the crash much less severe. As the gigacast begins crushing, the safety restraints are deployed.

As Wes points out in his post - you can see how accurate the virtual analysis and modeling were. The video shows the simulated crash side by side with the real-life crash test and they’re almost identical. All that virtual testing helps provide feedback into the loop to design a better and safer system - one that is uniquely different than any other vehicle on the road.

All the armchair experts claimed the Cybertruck has no crumple zone and I get it, the proportions seem impossible. It was a tough one and there is a lot of engineering that went into it. Let me break it down for you:

Here you can see the large single piece casting in action in a… https://t.co/Jk4X5erTcm pic.twitter.com/24Nmb1bmU5

— Wes (@wmorrill3) February 20, 2025

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Tesla Eliminates Front Casting on New Model Y; Improves Rear Casting

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Tesla has pioneered the use of single-piece castings for the front and rear sections of their vehicles, thanks to its innovative Gigapress process. Many automakers are now following suit, as this approach allows the crash structure to be integrated directly into the casting.

This makes the castings not only safer but also easier to manufacture in a single step, reducing costs and improving repairability. For example, replacing the entire rear frame of a Cybertruck is estimated to cost under $10,000 USD, with most of the expense coming from labor, according to estimates shared on X after high-speed rear collisions.

These insights come from Sandy Munro’s interview (posted below) with Lars Moravy, Tesla’s VP of Vehicle Engineering, highlighting how these advancements contribute to the improvements in Tesla’s latest vehicles, including the New Model Y.

However, with the new Model Y, Tesla has decided to go a different route and eliminated the front gigacast.

No Front Casting

Tesla’s factories aren’t equipped to produce both front and rear castings for the Model Y. Only Giga Texas and Giga Berlin used structural battery packs, but these were quickly phased out due to the underwhelming performance of the first-generation 4680 battery.

Tesla has gone back to building a common body across the globe, increasing part interchangeability and reducing supply chain complexity across the four factories that produce the Model Y. They’ve instead improved and reduced the number of unique parts up front to help simplify assembly and repair.

There is still potential for Tesla to switch back to using a front and rear casting - especially with their innovative unboxed assembly method. However, that will also require Tesla to begin using a structural battery pack again, which could potentially happen in the future with new battery technology.

Rear Casting Improvements

The rear casting has been completely redesigned, shedding 7 kg (15.4 lbs) and cutting machining time in half. Originally weighing around 67 kg (147 lbs), the new casting is now approximately 60 kg (132 lbs).

This 15% weight reduction improves both vehicle dynamics and range while also increasing the rear structure’s stiffness, reducing body flex during maneuvers.

Tesla leveraged its in-house fluid dynamics software to optimize the design, resulting in castings that resemble organic structures in some areas and flowing river patterns in others. Additionally, manufacturing efficiency has dramatically improved—the casting process, which originally took 180 seconds per part, has been reduced to just 75 seconds, a nearly 60% time reduction per unit.

Advancements in die-casting machines and cooling systems have allowed @Tesla to dramatically reduce cycle times and improve dimensional stability. pic.twitter.com/WB5ji67rvV

— Munro Live (@live_munro) March 11, 2025

New Casting Methods

Tesla’s new casting method incorporates conformal cooling, which cools the die directly within the gigapress. Tesla has been refining the die-casting machines and collaborating with manufacturers to improve the gigapress process.

In 2023, Tesla patented a thermal control unit for the casting process. This system uses real-time temperature analysis and precise mixing of metal streams to optimize casting quality. SETI Park, which covers Tesla’s manufacturing patents on X, offers a great series for those interested in learning more.

The new system allows Tesla to control the flow of cooling liquid, precisely directing water to different parts of the die, cooling them at varying rates. This enables faster material flow and quicker cooling, improving both dimensional stability and the speed of removing the part from the press for the next stage.

With these new process improvements, Tesla now rolls out a new Model Y at Giga Berlin, Giga Texas, and Fremont every 43 seconds—an astounding achievement in auto manufacturing. Meanwhile, Giga Shanghai operates two Model Y lines, delivering a completed vehicle every 35 seconds.

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