News
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.
Investor's Corner
Elon Musk drops a Thanksgiving hint about Starship’s biggest test yet
Elon Musk says Starship Flight 15 will try to catch the ship itself, a first.
Elon Musk says SpaceX’s next Starship flight will try something nobody has done before, by catching the ship itself. Speaking to roughly 2,000 people at the X Takeover event at Giga Texas on Saturday, Musk said Flight 15 is about four to six weeks away and “probably launches a little bit before Thanksgiving, is my guess.”
That is a slip from earlier reporting, which had pointed to a launch as early as October 19. Musk explained why the date keeps moving. “We’re making a bunch of improvements to the rocket between every flight,” he said, adding that there are often hundreds, sometimes thousands, of small changes. This time the list is short, “but some of them take a fair bit of work and we’ve got to go inside the tank to make some of these changes.”
“We’re going to try to catch the ship, which is a super big deal,” Musk said. “If we do so, that’ll be the first time that there’s been full recovery of an orbital class rocket.” SpaceX has already caught the Super Heavy booster with the tower’s mechanical arms, and has talked about catching the ship since late 2025, but the upper stage has never been caught.
Musk also laid out what comes after. “The next big milestone would be to refly both the booster and the ship,” he said, describing a Flight 16 where “all parts of an orbital rocket are reflown.”
The reason SpaceX wants this comes down to cost and cadence. Every Starship ship so far has ended its flight in the ocean, and SpaceX expects most of those water landings to end in fireballs. A ship that returns to Starbase intact can be inspected and flown again. SpaceX’s IPO filing, says Starship V3 is designed to deliver 100 metric tons to orbit in a fully reusable configuration, that SpaceX aims to cut the cost to reach orbit by 99% or more versus the historical average, and that tower catches should allow “multiple launches per day.”
The payoff goes beyond cheaper launches. The next generation Starlink V3 satellites are too large for Falcon 9 and can only fly on Starship, which can carry up to 60 per flight. Flight 14 on September 28 deployed the first 26 of them after Starship reached orbit despite an early engine shutdown, as Teslarati reported. Musk blamed engine computer software, and said the heat shield “was extremely robust,” which he claimed in August had solved Starship’s biggest challenge.
NASA’s Moon plans depend on the same capability. NASA’s inspector general has described a lander mission that needs a propellant depot in low Earth orbit and more than 10 tanker flights, with SpaceX targeting one tanker launch every six days. That schedule only works if ships and boosters come back fast and fly again. Also, ship to ship propellant transfer has not been attempted yet.
One interesting hurdle yet to be explored is bringing the ship back to the launch site, with reentry over land, which will undoubtedly come with a lot of aviation safety reviews.
Lifestyle
Tesla’s mirrorless Cybercab will give riders a visibility upgrade
Tesla engineer confirms Cybercab update letting riders pull up rear and repeater cameras on demand.
Tesla is working on a Cybercab update that would let passengers pull up the vehicle’s rear and side cameras on demand, and the request came straight from a rider.
The exchange played out on X late Friday. Cybercab rider Dan Burkland shared photos of the two-seater’s cabin screen after an evening ride, praised the UI team’s work, and left one request: let riders open the rear and repeater cameras whenever they want, “especially for peace of mind.” Tesla UI software engineer Evan (@CarCoder) answered with two words: “In development.”
The Tesla UI team absolutely crushed it with the infotainment software. Nicely done @CarCoder!
One feature request: Allow folks to pull up the rear & repeater cameras on demand. This would be great especially for peace of mind. https://t.co/mNAOSLx6pE
— Dan Burkland (@DBurkland) October 10, 2026
The idea fits a pattern Teslarati has tracked since public rides began. Days after paid Cybercab service opened in Austin, Tesla sent riders a survey that asked them to rate the touchscreen, the app and the cabin, and to pick the features they wanted most. We reported on that survey in September, and a camera view is the kind of small software change Tesla can push quickly if riders keep asking.
It also speaks to something unique about the vehicle. With no steering wheel, no pedals and no driver, passengers have no mirror to check and no way to see behind them. The hardware is clearly built for camera awareness, from the repeater cameras to the rear camera. Letting a passenger look through those same cameras would give a nervous first time rider a way to confirm what is around the car.
The timing matters because the fleet is growing fast. Tesla’s Robotaxi account said on Saturday that more than 300 Cybercabs are now serving Austin, an eightfold increase in 30 days, and Tesla AI chief Ashok Elluswamy named Dallas as the next city. More cars and more cities mean more people riding in a driverless vehicle for the first time, which is exactly when small trust features carry weight.
For now, the feature is confirmed only as in development. If Tesla follows its usual pattern with Cybercab software, riders could see it appear in a point release without any announcement, and Teslarati will watch for it.
News
Tesla’s Cybercab fleet jumped 8x in a month, with Dallas up next
Tesla confirms its first official Cybercab fleet number as Austin scales fast and Dallas looms.
Tesla says more than 300 Cybercabs are now serving Austin, the first time the company has put an official number on its active Cybercab fleet. The figure came from the Robotaxi account on X on Saturday, which wrote that one month after launch the service had “scaled to 300+ Cybercabs serving Austin – an 8x increase in 30 days.”
Ashok Elluswamy, Tesla’s head of AI software, quoted the post with a line that carried the bigger news. “Two years since the 10/10 Cybercab WeRobot event, the cabs are everywhere in Austin now. Dallas soon,” he wrote. It is the first time Tesla has named the next city for public Cybercab rides.
One month after launch, we’ve scaled to 300+ Cybercabs serving Austin – an 8x increase in 30 days https://t.co/EagJy2JAsm
— Robotaxi (@robotaxi) October 10, 2026
Tesla opened Cybercab rides to the public in Austin on September 4, as Teslarati reported, a day after an invite only launch event. The ramp since then has been steep. Our September 28 report had the fleet at well over 100 units after availability jumped from 58 to 125 in a single week. On Thursday, Tesla added 150 Cybercabs to the Texas automated vehicle registry, lifting its registered count to 319 from 169. The first seven appeared on the registry on August 31.
RobotaxiTracker, a community site that counts vehicles from sightings and state records, listed 275 vehicles in unsupervised service in Austin on Saturday, 105 of them Cybercabs, which is well below Tesla’s figure. Tracker counts can lag official numbers, though Sawyer Merritt noted that Cybercab wait times in Austin stayed short on Saturday evening even with more than 2,000 fans in town for X Takeover.
Regulators are watching the rollout. NHTSA opened an audit query into Tesla’s certification that the Cybercab meets federal safety standards, and sworn answers are due October 30. Tesla reports third quarter earnings on October 21, which gives the company a natural venue to define its fleet numbers and put a date on Dallas.
Elon Musk drops a Thanksgiving hint about Starship’s biggest test yet
Tesla’s mirrorless Cybercab will give riders a visibility upgrade
Tesla’s Cybercab fleet jumped 8x in a month, with Dallas up next
The Pentagon taps Elon Musk to design the battlefield of the future
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