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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Tesla appears to be preparing to expand its Robotaxi geofence in Austin, Texas, with numerous engineering vehicles taking to the road. One of the most interesting sights, between the short and tall LiDAR rigs, was a Cybertruck validation vehicle, which we don’t often see.
Tesla’s expansion is moving the Robotaxi Network into downtown Austin, a dense urban environment that is currently outside the geofence. It appears Tesla is content with the latest builds of Robotaxi FSD and is ready to take on urban traffic.
The inclusion of a Cybertruck in the validation fleet is noteworthy, as the rest of the vehicles are Model Ys. This suggests that Tesla may be addressing two challenges simultaneously: expanding its service area while also addressing the FSD gap between the Cybertruck and other HW4 Tesla vehicles.
Tesla Validating Downtown Austin before expanding the Robotaxi geo-fence area. pic.twitter.com/ylFATtjcDi
Recent sightings have shown a fleet of Tesla vehicles, equipped with rooftop validation sensor rigs, running routes throughout downtown Austin and across the South Congress Bridge. While these rigs include LiDAR, it’s not a sign that Tesla is abandoning its vision-only approach.
Instead, Tesla uses the high-fidelity data from the LiDAR as a ground truth measurement to validate and improve the performance of its cameras. In short, it essentially uses the LiDAR measurements as the actual distances and then compares the distances determined in vision-only to the LiDAR measurements. This allows Tesla to tweak and improve its vision system without needing LiDAR.
This data collection in a new, complex environment right outside the Robotaxi geofence is an indicator that plans to expand the geofence. Tesla has previously indicated that they intend to roll out more vehicles and expand the geofence slowly. Given that their operational envelope includes the entire Austin Metro Area, we can expect more locations to open up gradually.
Once they expand the operational radius to include downtown Austin, they will likely also have to considerably increase the number of Robotaxis active in the fleet at any given time. Early-access riders are already saying that the wait time for a Robotaxi is too long, with them sometimes having to wait 15 minutes to be picked up.
With a larger service area, we expect Tesla to also increase the number of vehicles and the number of invited riders to try out the service.
After all, Tesla’s goal is to expand the Robotaxi Network to multiple cities within the United States by the end of 2025. Tesla has already been running an employees-only program in California, and we’ve seen validation vehicles as far away as Boston and New Jersey, on the other side of the country.
Cyber FSD Lagging Behind
One of the most significant details from these recent sightings is the presence of a Cybertruck. Cybertruck’s FSD builds have famously lagged behind the builds available on the rest of Tesla’s HW4 fleet. Key features that were expected never fully materialized for the Cybertruck, and the list of missing features is quite extensive.
Start FSD from Park
Improved Controller
Reverse on FSD
Actually Smart Summon
It may not look like a lot, but if you drive a Cybertruck on FSD and then hop in any of the rest of Tesla’s HW4 vehicles, you’ll notice a distinct difference. This is especially evident on highways, where the Cybertruck tends to drift out of the lane, often crossing over the lane markings.
Tesla was testing parts of Downtown Austin, TX with this Cybertruck which had a massive roof rack, and sensors.
We previously released an exclusive mentioning that a well-positioned internal source confirmed with us that a new FSD build for the Cybertruck was upcoming, but we never ended up receiving that particular build, only a point release to V13.2.9. The AI team’s focus had clearly shifted to getting the latest Robotaxi builds running and validated, and while a flagship, the Cybertruck fleet was small and new, and really a secondary task.
The Cybertruck’s larger size, steer-by-wire, rear-wheel steering, and different camera placements likely present a bigger set of challenges for FSD. Deploying it now as a validation vehicle in a complex environment like downtown Austin suggests that Tesla is finally gathering the specific data needed to bring the Cybertruck’s capabilities up to par. This focused effort is likely the necessary step to refine FSD’s handling of the Cybertruck before they begin rolling out new public builds.
When?
Once Tesla’s validation is complete, we can probably expect the Robotaxi Network to expand its borders for the first time in the coming days or weeks. However, we’ll likely see more signs of the expansion, such as Robotaxi vehicles driving themselves around the area, before the expansion actually happens.
Hopefully, the Cybertruck will also learn from its older siblings and receive the rest of its much-needed FSD features, alongside an FSD update for the entire fleet.
Tesla is rolling out a fairly big update for its iOS and early-access-only Robotaxi app, delivering a suite of improvements that address user feedback from the initial launch last month. The update improves the user experience with increased flexibility, more information, and overall design polish.
The most prominent feature in this update is that Tesla now allows you to adjust your pickup location. Once a Robotaxi arrives at your pickup location, you have 15 minutes to start the ride. The app will now display the remaining time your Robotaxi will wait for you, counting down from 15:00. The wait time is also shown in the iOS Live Activity if your phone is on the lock screen.
How Adjustable Pickups Work
We previously speculated that Tesla had predetermined pickup locations, as the pickup location wasn’t always where the user was. Now, with the ability to adjust the pickup location, we can clearly see that Tesla has specific locations where users can be picked up.
Rather than allowing users to drop a pin anywhere on the map, the new feature works by having the user drag the map to their desired area. The app then presents a list of nearby, predetermined locations to choose from. Once a user selects a spot from this curated list, they hit “Confirm.” The pickup site can also be changed while the vehicle is en route.
This specific implementation raises an interesting question: Why limit users to predetermined spots? The answer likely lies in how Tesla utilizes fleet data to improve its service.
Here is the new Tesla Robotaxi pickup location adjustment feature.
While the app is still only available on iOS through Apple’s TestFlight program, invited users can download and update the app.
Tesla included these release notes in update 25.7.0 of the Robotaxi app:
You can now adjust pickup location
Display the remaining wait time at pickup in the app and Live Activity
Design improvements
Bug fixes and stability improvements
Nic Cruz Patane
Why Predetermined Pick Up Spots?
The use of predetermined pickup points is less of a limitation and more of a feature. These curated locations are almost certainly spots that Tesla’s fleet data has identified as optimal and safe for an autonomous vehicle to perform a pickup or drop-off.
This suggests that Tesla is methodically “mapping” its service area not just for calibration and validation of FSD builds but also to help perform the first and last 50-foot interactions that are critical to a safe and smooth ride-hailing experience.
An optimal pickup point likely has several key characteristics identified by the fleet, including:
A safe and clear pull-away area away from traffic
Good visibility for cameras, free of obstructions
Easy entry and exit paths for an autonomous vehicle
This change to pick-up locations reveals how Tesla’s Robotaxi Network is more than just Unsupervised FSD. There are a lot of moving parts, many of which Tesla recently implemented, and others that likely still need to be implemented, such as automated charging.
Frequent Updates
This latest update delivers a much-needed feature for adjusting pickup locations, but it also gives us a view into exactly what Tesla is doing with all the data it is collecting with its validation vehicles rolling around Austin, alongside its Robotaxi fleet.
Tesla is quickly iterating on its app and presumably the vehicle’s software to build a reliable and predictable network, using data to perfect every aspect of the experience, from the moment you hail the ride to the moment you step out of the car.
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