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Tesla FSD Beta 10.69 release notes highlight better left turns, smoother driving
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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Tesla seeks approval to test FSD Supervised in new Swedish city
Tesla has applied to conduct local Full Self-Driving (Supervised) testing in the city of Jönköping, Sweden.
Tesla has applied to conduct local Full Self-Driving (Supervised) testing in the city of Jönköping, Sweden.
As per local outlet Jönköpings-Posten, Tesla has contacted the municipality with a request to begin FSD (Supervised) tests in the city. The company has already received approval to test its Full Self-Driving (Supervised) software in several Swedish municipalities, as well as on the national road network.
Sofia Bennerstål, Tesla’s Head of Public Policy for Northern Europe, confirmed that an application has been submitted for FSD’s potential tests in Jönköping.
“I can confirm that we have submitted an application, but I cannot say much more about it,” Bennerstål told the news outlet. She also stated that Tesla is “satisfied with the tests” in the region so far.
The planned tests in Jönköping would involve a limited number of Tesla-owned vehicles. Trained Tesla safety drivers would remain behind the wheel and be prepared to intervene if necessary.
Tesla previously began testing in Nacka municipality after receiving local approval. At the time, the company stated that cooperation between authorities, municipalities, and industry enables technological progress and helps integrate future transport systems into real-world traffic conditions, as noted in an Allt Om Elbil report.
If approved, Jönköping would become the latest Swedish municipality to allow local Full Self-Driving (Supervised) testing.
Tesla’s Swedish testing program is part of the company’s efforts to validate its supervised autonomous driving software in everyday traffic environments. Municipal approvals allow Tesla to gather data in urban settings that include roundabouts, complex intersections, and mixed traffic conditions.
Sweden has become an increasingly active testing ground for Tesla’s driver-assistance software in Europe, with regulatory coordination between local authorities and national agencies enabling structured pilot programs.
Elon Musk
Microsoft partners with Starlink to expand rural internet access worldwide
The update was shared ahead of Mobile World Congress.
Microsoft has announced a new collaboration with Starlink as part of its expanding digital access strategy, following the company’s claim that it has extended internet connectivity coverage to more than 299 million people worldwide.
The update was shared ahead of Mobile World Congress, where Microsoft detailed how it surpassed its original goal of bringing internet access to 250 million people by the end of 2025.
In a blog post, Microsoft confirmed that it is now working with Starlink to expand connectivity in rural and hard-to-reach regions.
“Through our collaboration with Starlink, Microsoft is combining low-Earth orbit satellite connectivity with community-based deployment models and local ecosystem partnerships,” the company wrote.
The partnership is designed to complement Microsoft’s existing work with local internet providers and infrastructure companies across Africa, Latin America, and India, among other areas. Microsoft noted that traditional infrastructure alone cannot meet demand in some regions, making low-Earth orbit satellite connectivity an important addition.
Kenya was cited as an early example. Working with Starlink and local provider Mawingu Networks, Microsoft is supporting connectivity for 450 community hubs in rural and underserved areas. These hubs include farmer cooperatives, aggregation centers, and digital access facilities intended to support agricultural productivity and AI-enabled services.
Microsoft stated that 2.2 billion people globally remain offline, and that connectivity gaps risk widening as AI adoption accelerates.
Starlink’s expanding constellation, now numbering more than 9,700 satellites in orbit, provides near-global coverage, making it one of the few systems capable of delivering broadband to remote regions without relying on terrestrial infrastructure.
Starlink is expected to grow even more in the coming years as well, especially as SpaceX transitions its fleet to Starship, which is capable of carrying significantly larger payloads compared to its current workhorse, the Falcon 9.
Elon Musk
Tesla expands US LFP battery supply with LG Energy Solution deal: report
The report was initially published by TheElec, citing industry sources.
LG Energy Solution (LGES) will manufacture lithium iron phosphate (LFP) energy storage system (ESS) batteries for Tesla at its Lansing, Michigan facility.
The report was initially published by TheElec, citing industry sources.
LG Energy Solution’s Lansing plant, formerly known as Ultium Cells 3, was previously operated as a joint venture with General Motors. LGES acquired GM’s stake in May 2025 and now fully owns the site. With a production capacity of 50 GWh per year, it is one of the company’s largest facilities in North America.
LG Energy Solution is converting part of the Lansing factory to produce LFP batteries for energy storage systems. Equipment orders for the new lines have already been placed, and mass production is reportedly expected to begin in the second half of next year.
Last July, LG Energy Solution disclosed a 5.94 trillion won battery supply agreement running from August 2027 to July 2030. While the company did not name the customer, industry sources pointed to Tesla as the buyer.
Tesla has primarily used CATL’s prismatic batteries for its Megapack systems. The move to source prismatic LFP cells from LG Energy Solution’s U.S. plant could then be seen as part of Tesla’s efforts to bolster its North American supply base for its energy storage business.
For the Lansing conversion, LG Energy Solution reportedly plans to use electrode equipment originally ordered under its Ultium Cells venture with General Motors. Suppliers reportedly include CIS and Hirano Tecseed for electrode systems, TSI for mixing equipment, CK Solution for heat exhaust systems, A-Pro for formation equipment, and Shinjin Mtech for assembly kits.
Tesla currently manufactures energy storage products at facilities in California and Shanghai, though another Megafactory that produces the Megapack is also expected to be built in Texas. As per recent reports, the Texas Megafactory recently advanced with a major property sale.
Tesla seeks approval to test FSD Supervised in new Swedish city
Microsoft partners with Starlink to expand rural internet access worldwide
