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Tesla FSD Beta 10.69 release notes highlight better left turns, smoother driving

(Credit: Tesla)

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3 years ago

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Tesla released FSD Beta 10.69 to the first round of testers over the weekend. Read v.10.69’s release notes below to check out the latest improvements. 

Stay in your Lanes

  • Added a new “deep lane guidance” module to the Vector Lanes neural network which fuses features extracted from the video streams with coarse map data, i.e. lane counts and lane connectivites. This architecture achieves a 44% lower error rate on lane topology compared to the previous model, enabling smoother control before lanes and their connectivities becomes visually apparent. This provides a way to make every Autopilot drive as good as someone driving their own commute, yet in a sufficiently general way that adapts for road changes.

 Nothing Like Smooth Driving

  • Improved overall driving smoothness, without sacrificing latency, through better modeling of system and actuation latency in trajectory planning. Trajectory planner now independently accounts for latency from steering commands to actual steering actuation, as well as acceleration and brake commands to actuation. This results in a trajectory that is a more accurate model of how the vehicle would drive. This allows better downstream controller tracking and smoothness while also allowing a more accurate response during harsh manevuers.
  • Increased smoothness for protected right turns by improving the association of traffic lights with slip lanes vs yield signs with slip lanes. This reduces false slowdowns when there are no relevant objects present and also improves yielding position when they are present.
  • Reduced false slowdowns near crosswalks. This was done with improved understanding of pedestrian and bicyclist intent based on their motion.
  • Enabled creeping for visibility at any intersection where objects might cross ego’s path, regardless of presence of traffic controls.
  • Improved accuracy of stopping position in critical scenarios with crossing objects, by allowing dynamic resolution in trajectory optimization to focus more on areas where finer control is essential.
  • Reduced latency when starting from a stop by accounting for lead vehicle jerk.

Chuck’s Left Turn

  • Improved unprotected left turns with more appropriate speed profile when approaching and exiting median crossover regions, in the presence of high speed cross traffic (“Chuck Cook style” unprotected left turns). This was done by allowing optimizable initial jerk, to mimic the harsh pedal press by a human, when required to go in front of high speed objects. Also improved lateral profile approaching such safety regions to allow for better pose that aligns well for exiting the region. Finally, improved interaction with objects that are entering or waiting inside the median crossover region with better modeling of their future intent.

Safety is Number 1

  • Added control for arbitrary low-speed moving volumes from Occupancy Network. This also enables finer control for more precise object shapes that cannot be easily represented by a cuboid primitive. This required predicting velocity at every 3D voxel. We may now control for slow-moving UFOs.
  • Made speed profile more comfortable when creeping for visibility, to allow for smoother stops when protecting for potentially occluded objects.
  • Improved speed when entering highway by better handling of upcoming map speed changes, which increases the confidence of merging onto the highway.
  • Enabled faster identification of red light runners by evaluating their current kinematic state against their expected braking profile.

Tesla FSD “Brain” Improvements

  • Upgraded Occupancy Network to use video instead of images from single time step. This temporal context allows the network to be robust to temporary occlusions and enables prediction of occupancy flow. Also, improved ground truth with semantics-driven outlier rejection, hard example mining, and increasing the dataset size by 2.4x.
  • Upgraded to a new two-stage architecture to produce object kinematics (e.g. velocity, acceleration, yaw rate) where network compute is allocated O(objects) instead of O(space). This improved velocity estimates for far away crossing vehicles by 20%, while using one tenth of the compute.
  • Improved geometry error of ego-relevant lanes by 34% and crossing lanes by 21% with a full Vector Lanes neural network update. Information bottlenecks in the network architecture were eliminated by increasing the size of the per-camera feature extractors, video modules, internals of the autoregressive decoder, and by adding a hard attention mechanism which greatly improved the fine position of lanes.
  • Improved recall of animals by 34% by doubling the size of the auto-labeled training set.
  • Increased recall of forking lanes by 36% by having topological tokens participate in the attention operations of the autoregressive decoder and by increasing the loss applied to fork tokens during training.
  • Improved velocity error for pedestrians and bicyclists by 17%, especially when ego is making a turn, by improving the onboard trajectory estimation used as input to the neural network.
  • Improved recall of object detection, eliminating 26% of missing detections for far away crossing vehicles by tuning the loss function used during training and improving label quality.
  • Improved object future path prediction in scenarios with high yaw rate by incorporating yaw rate and lateral motion into the likelihood estimation. This helps with objects turning into or away from ego’s lane, especially in intersections or cut-in scenarios.

Tesla is rolling out FSD Beta v.10.69 in phases, starting with ~1,000 testers over the weekend. Once the update is rolled out for wide release, the price of FSD Beta will increase.

The Teslarati team would appreciate hearing from you. If you have any tips, contact me at maria@teslarati.com or via Twitter @Writer_01001101.

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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 adds new feature that will be great for crowded parking situations

This is the most recent iteration of the app and was priming owners for the slowly-released Holiday Update.

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1 hour ago

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December 10, 2025

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Credit: Grok

Tesla has added a new feature that will be great for crowded parking lots, congested parking garages, or other confusing times when you cannot seem to pinpoint where your car went.

Tesla has added a new Vehicle Locator feature to the Tesla App with App Update v4.51.5.

This is the most recent iteration of the app and was priming owners for the slowly-released Holiday Update.

While there are several new features, which we will reveal later in this article, perhaps one of the coolest is that of the Vehicle Locator, which will now point you in the direction of your car using a directional arrow on the home screen. This is similar to what Apple uses to find devices:

In real time, the arrow gives an accurate depiction of which direction you should walk in to find your car. This seems extremely helpful in large parking lots or unfamiliar shopping centers.

Getting to your car after a sporting event is an event all in itself; this feature will undoubtedly help with it:

Tesla’s previous app versions revealed the address at which you could locate your car, which was great if you parked on the street in a city setting. It was also possible to use the map within the app to locate your car.

However, this new feature gives a more definitive location for your car and helps with the navigation to it, instead of potentially walking randomly.

It also reveals the distance you are from your car, which is a big plus.

Along with this new addition, Tesla added Photobooth features, Dog Mode Live Activity, Custom Wraps and Tints for Colorizer, and Dashcam Clip details.

All in all, this App update was pretty robust.

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Elon Musk

Tesla CEO Elon Musk shades Waymo: ‘Never really had a chance’

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2 hours ago

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December 10, 2025

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Credit: Tesla

Tesla CEO Elon Musk shaded Waymo in a post on X on Wednesday, stating the company “never really had a chance” and that it “will be obvious in hindsight.”

Tesla and Waymo are the two primary contributors to the self-driving efforts in the United States, with both operating driverless ride-hailing services in the country. Tesla does have a Safety Monitor present in its vehicles in Austin, Texas, and someone in the driver’s seat in its Bay Area operation.

Musk says the Austin operation will be completely void of any Safety Monitors by the end of the year.

With the two companies being the main members of the driverless movement in the U.S., there is certainly a rivalry. The two have sparred back and forth with their geofences, or service areas, in both Austin and the Bay Area.

While that is a metric for comparison now, ultimately, it will not matter in the coming years, as the two companies will likely operate in a similar fashion.

Waymo has geared its business toward larger cities, and Tesla has said that its self-driving efforts will expand to every single one of its vehicles in any location globally. This is where the true difference between the two lies, along with the fact that Tesla uses its own vehicles, while Waymo has several models in its lineup from different manufacturers.

The two also have different ideas on how to solve self-driving, as Tesla uses a vision-only approach. Waymo relies on several things, including LiDAR, which Musk once called “a fool’s errand.”

This is where Tesla sets itself apart from the competition, and Musk highlighted the company’s position against Waymo.

Jeff Dean, the Chief Scientist for Google DeepMind, said on X:

“I don’t think Tesla has anywhere near the volume of rider-only autonomous miles that Waymo has (96M for Waymo, as of today). The safety data is quite compelling for Waymo, as well.”

Musk replied:

“Waymo never really had a chance against Tesla. This will be obvious in hindsight.”

Tesla stands to have a much larger fleet of vehicles in the coming years if it chooses to activate Robotaxi services with all passenger vehicles. A simple Over-the-Air update will activate this capability, while Waymo would likely be confined to the vehicles it commissions as Robotaxis.

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News

Tesla supplier Samsung preps for AI5 production with latest move

According to a new report from Sedaily, Samsung is accelerating its preparation for U.S. production of the AI5 chips by hiring veteran engineers for its Customer Engineering team.

Published

3 hours ago

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December 10, 2025

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Credit: Tesla

Tesla supplier Samsung is preparing to manufacture the AI5 chip, which will launch the company’s self-driving efforts even further, with its latest move.

According to a new report from Sedaily, Samsung is accelerating its preparation for U.S. production of the AI5 chips by hiring veteran engineers for its Customer Engineering team, which will help resolve complex foundry challenges, stabilize production and yields, and ensure manufacturing goes smoothly for the new project.

The hiring push signals that Tesla’s AI5 project is moving forward quickly at Samsung, which was one of two suppliers to win a contract order from the world’s leading EV maker.

TSMC is the other. TSMC is using its 3nm process, reportedly, while Samsung will do a 2nm as a litmus test for the process.

The different versions are due to the fact that “they translate designs to physical form differently,” CEO Elon Musk said recently. The goal is for the two to operate identically, obviously, which is a challenge.

Some might remember Apple’s A9 “Chipgate” saga, which found that the chips differed in performance because of different manufacturers.

The AI5 chip is Tesla’s next-generation hardware chip for its self-driving program, but it will also contribute to the Optimus program and other AI-driven features in both vehicles and other projects. Currently, Tesla utilizes AI4, formerly known as HW4 or Hardware 4, in its vehicles.

Tesla teases new AI5 chip that will revolutionize self-driving

AI5 is specialized for use by Tesla as it will work in conjunction with the company’s Neural Networks, focusing on real-time inference to make safe and logical decisions during operation.

Musk said it was an “amazing design” and an “immense jump” from Tesla’s current AI4 chip. It will be roughly 40 times faster, and have 8 times the raw compute, with 9 times the memory capacity. It is also expected to be three times as efficient per watt as AI4.

AI5 will make its way into “maybe a small number of units” next year, Musk confirmed. However, it will not make its way to high-volume production until 2027. AI5 is not the last step, either, as Musk has already confirmed AI6 would likely enter production in mid-2028.

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