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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 expands Robotaxi in a way that was long anticipated
Instead, it has to do with the consumer base it offers Robotaxi to, because it has not offered it to everyone in the past.
Tesla has expanded Robotaxi in a way that was long anticipated, and it does not have to do with a new, larger geofence in a city where it already offered its partially autonomous ride-hailing suite, or a new city altogether.
Instead, it has to do with the consumer base it offers Robotaxi to, because it has not offered it to everyone in the past.
Tesla has taken a major step forward in its autonomous ride-hailing ambitions with the official launch of the Tesla Robotaxi app for Android users. Released on the Google Play Store on April 24. Titled simply “Tesla Robotaxi,” the app is now available to download directly from Tesla.
The @Tesla Robtoaxi App has just officially launched for Android users. Go get some rides y’all!
Download: https://t.co/D2jIONXc91 pic.twitter.com/rQ6TD14zkC
— Sawyer Merritt (@SawyerMerritt) April 24, 2026
This rollout fulfills a long-anticipated expansion that opens the service to hundreds of millions of Android smartphone users who were previously unable to access it on iOS alone.
The app delivers a streamlined, driverless ride experience powered by Tesla’s automated driving technology.
Users sign in with a Tesla Account, view the current service area map within the app, enter a destination, and receive an estimated fare and arrival time before confirming the ride. When a Model Y from the Robotaxi fleet arrives, riders confirm the license plate, enter the vehicle, fasten their seatbelt, and tap “Start Ride” on either the app or the vehicle’s touchscreen.
During the trip, passengers have access to all the same controls that iOS users do, and can adjust climate settings, seat positions, and music while tracking progress on an in-app map. The interface also allows drop-off changes or support requests if needed. After the ride, users exit, close the doors, and submit feedback.
This Android availability directly broadens the rider base for Robotaxi in its initial service areas. Unfortunately, Android users are used to being subject to delayed launches of new features available to Tesla owners.
By removing the iOS-only barrier, Tesla instantly expands the addressable market, enabling far more people to summon and use the autonomous vehicles already operating on public roads.
The move is a foundational requirement for scaling ride volume and gathering the real-world data needed to refine the unsupervised Full Self-Driving system that powers every trip.
For the Robotaxi program itself, the launch signals steady operational progress. It prepares the service for higher utilization rates as the fleet grows and supports the transition from limited early deployments to a more robust network.
Tesla expands Unsupervised Robotaxi service to two new cities
Tesla has indicated that users outside current service areas can sign up at the company’s website for future notifications, pointing to a deliberate, phased geographic rollout.
Looking ahead, the company plans to incorporate Cybercab vehicles to increase fleet capacity and efficiency while continuing to expand service territories. With the Android app now live, Tesla has removed a key adoption hurdle and positioned Robotaxi for the next phase of growth in autonomous urban transportation.
The infrastructure is now in place to support significantly larger rider demand as production and deployment accelerate.
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UPDATE: SpaceX’s Falcon Heavy that launched a Tesla into space is back on a mission
SpaceX Falcon Heavy returns after 18 months away to deliver a satellite that only it could carry.
UPDATE: 10:29 a.m. et: SpaceX is standing down from today’s Falcon Heavy launch of the ViaSat-3 F3 mission due to unfavorable weather. A new target date will be shared once confirmed.
After an 18-month absence, SpaceX’s Falcon Heavy is returning to mission on Monday morning when it’s scheduled to lift off from Launch Complex 39A at Kennedy Space Center at 10:21 a.m. EDT.
The mission is called ViaSat-3 F3, and the heavy satellite payload needs to reach geostationary orbit, sitting 22,236 miles above Earth where its speed matches the planet’s rotation. Getting a satellite that heavy to that altitude demands more thrust than a single-core Falcon 9 can deliver.
This marks the Falcon Heavy’s 12th flight overall since its debut in February 2018, and its first since NASA’s Europa Clipper mission in October 2024.
Arguably, the most exciting element for spectators will be watching the booster recoveries in action when the two side boosters, B1072 and B1075, will attempt simultaneous landings at Landing Zone 2 and the newer Landing Zone 40 at Cape Canaveral Space Force Station, while the center core will be expended over the ocean.
SpaceX wins its first MARS contract but it comes with a catch
Following satellite deployment, expected roughly five hours after launch, ViaSat-3 F3 will spend several months traveling to its final orbital slot before undergoing in-orbit testing, with service entry expected by late summer 2026
As Teslarati reported, NASA awarded SpaceX a $175.7 million contract on April 16, 2026, to launch the ESA Rosalind Franklin Mars rover aboard a Falcon Heavy no earlier than late 2028, which would mark the first time SpaceX has ever sent a payload to Mars. That contract came on top of an already deep pipeline that includes the Roman Space Telescope, the Dragonfly Saturn mission, and multiple national security payloads.
SpaceX executed 165 missions in 2025 and now accounts for approximately 85% of all global orbital launches. With Starlink surpassing 10 million subscribers and an IPO targeting a $1.75 trillion valuation still ahead, Monday’s launch is one more data point in a company that has quietly become the backbone of both commercial and government space access worldwide.
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Tesla launches solution to end Supercharger fights once and for all
Tesla is launching its solution to end Supercharger fights once and for all, eliminating any confusion on who is to charge next at a congested location.
Last year, a notable incident at a Tesla Supercharger led to a fight, and it all stemmed from a disagreement over who arrived at the location first.
Congestion at Tesla Superchargers is a pretty infrequent occurrence for most of us, but there are more congested and popular areas where wait times can be extensive. An unfortunate growing pain of EV ownership is the plain fact that chargers are not as available as gas pumps, and there are, at times, lines to charge.
This can cause tensions to flare and people to get entitled when visiting Superchargers. Nobody wants to spend hours at a Supercharger, but now, there will be no more confusion when there is a queue, and that’s thanks to Tesla’s new Virtual Queue for Superchargers.
Tesla is finally starting to build out the Virtual Supercharger Queue, according to Not a Tesla App, but it still relies on drivers to make it work.
When a driver is near a Supercharger that is full, a message will pop up on the Tesla App, using the driver’s location to determine their eligibility to join the virtual queue.
The app states:
“While the app is closed, Tesla uses your location to notify you of accurate wait times at Superchargers when you arrive.”
Another message within the app states:
“There is a waitlist to charge. Are you sure you want to start a charging session now?”
This sounds as if it will require drivers to act appropriately and only plug in when the app prompts them to do so, by letting them know it is their turn.
The app will notify the driver of their position in the queue, as well as how many vehicles are ahead of them.
Tesla launches first ‘true’ East Coast V4 Supercharger: here’s what that means
The company announced a while back that it would be working on a solution for this issue. Personally, I’ve only had to wait at a Supercharger for a charge on one occasion, and there was a line of between 3 and 10 cars during this singular occurrence.
I’m out at the Lancaster, PA Supercharger and showed up with a queue of three vehicles.
It’s now up to five and there have been several issues with order of arrival and confusion about who is first.
Any update on Supercharger queue? @elonmusk @aelluswamy @r_jegaa
— TESLARATI (@Teslarati) January 31, 2026
There were no conflicts or arguments about who had arrived first, but there was some discussion between several drivers during my time there about who was to charge first. Throw a non-Tesla EV into the mix, one that can only charge at a pull-in spot, and that causes even more of a complication.