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

(Credit: Tesla)

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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.

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 is making sweeping improvements to Robotaxi

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Credit: Tesla

Tesla is continuing to refine and improve its Robotaxi program from A to Z, and it is now going to make some sweeping changes to the smartphone app portion of the suite.

The company is aiming to make some sweeping changes with the release of Robotaxi app version 26.4.5, which was recently decompiled by Tesla App Updates on X. The update reveals significant new code, focused on remote operations, safety protocols, and seamless autonomous ride-hailing.

These improvements evidently signal Tesla’s preparations for scaling unsupervised Cybercab deployments, particularly the steering wheel-less variants spotted in production. The enhancements emphasize providing a reliable experience that gives passengers support when needed, along with operational efficiency.

Remote Operator Voice Calls

One standout addition is support for remote operator voice calls. The app now includes a dedicated native voice-communication system linking passengers directly to Tesla teleoperators via the vehicle’s cabin microphone and speakers.

This feature allows real-time assistance during rides, addressing issues like navigation questions or comfort adjustments without disrupting the autonomous journey. It builds on existing support protocols, making human intervention more accessible and intuitive.

Proactive Remote Assistance

The update introduces proactive remote assistance capabilities. Rather than waiting for passenger-initiated requests, the system can anticipate and offer help based on monitored conditions.

This might include something like suggesting route changes, climate adjustments, or addressing potential delays. By integrating AI-driven monitoring with human oversight, Tesla aims to deliver a smoother, more attentive experience that exceeds traditional ride-sharing services.

Manual Override and Remote Start for Steering Wheel-less Cybercabs

A key highlight for the wheel-less Cybercab fleet is manual override plus remote start functionality. Fleet operators and technicians can now temporarily take control or remotely start vehicles lacking steering wheels. This is crucial for lower-speed maneuvers, such as getting vehicles from tight parking situations or even performing maintenance.

Controls are strictly limited for safety–typically to speeds under 2 MPH–ensuring these interventions remain emergency measures only.

Tesla is adding a secure “Enable Manual Drive” mode that will allow those fleet operators or others to take control temporarily.

Additionally, a Remote Start feature, which authorizes an empty vehicle to begin a driverless ride alone.

Ride-Hailing and Dispatch Features

Ride dispatch has been enhanced with soft-matching and multi-stop support. The app can intelligently pair riders with available Cybercabs while accommodating multiple destinations in a single trip.

This optimizes fleet utilization, reduces wait times, and improves efficiency for shared rides. Soft-matching likely considers factors like proximity, rider preferences, and vehicle availability for better user satisfaction.

Rider-Cabin Sync, Real-Time Routing

New synchronization tools allow the rider’s app to mirror and control cabin settings like seating, climate, and entertainment directly from their phone. Real-time routing updates adapt dynamically to traffic or road conditions, while dynamic safety monitoring continuously assesses the environment.

The app can now push updates directly to the main screen, enabling Center Display Control. Additionally, there is a dedicated navigation protocol sharing the exact coordinates of road closures and construction, which could prevent the car from getting stuck and needing manual override.

These features create a cohesive, responsive experience where the vehicle and app work in harmony.

Kill Switch

A high-security command lets Tesla completely freeze a vehicle’s ability to drive. This would take the vehicle out of the Robotaxi fleet for any reason Tesla sees fit, and would not allow it to be put into gear even with the correct equipment, like valid keys.

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SpaceX just forced Verizon, AT&T and T-Mobile to team up for the first time in history

AT&T, T-Mobile, and Verizon just joined forces for one reason: Starlink is winning.

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Starlink D2D direct to device vs Verizon, AT&T (Concept render by Grok)

America’s three largest wireless carriers, AT&T, T-Mobile, and Verizon, announced on On May 14, 2026 that they had agreed in principle to form a joint venture aimed at pooling their spectrum resources to expand satellite-based direct-to-device (D2D) connectivity across the United States in what can be seen as a direct response to SpaceX’s Starlink initiative. D2D, in plain terms, is technology that lets a standard smartphone connect directly to a satellite in orbit, the same way it connects to a cell tower, with no extra hardware required.

The alliance is widely seen as a means to slow Starlink’s rapid expansion in the satellite internet and mobile markets. SpaceX’s Starlink Mobile service launched commercially in July 2025 through a partnership with T-Mobile, starting with messaging before expanding to broadband data. SpaceX secured access to valuable wireless spectrum through its $17 billion deal with EchoStar, paving the way for significantly faster satellite-to-phone speeds.

The FCC just said ‘No’ to SpaceX for now

SpaceX was not shy about its reaction. SpaceX president and COO Gwynne Shotwell responded on X: “Weeeelllll, I guess Starlink Mobile is doing something right! It’s David and Goliath (X3) all over again — I’m bettin’ on David.” SpaceX’s VP of Satellite Policy David Goldman went further, flagging potential antitrust concerns and asking whether the DOJ would even allow three dominant competitors to coordinate in a market where a new rival is actively entering.


Financial analysts at LightShed Partners were blunt, saying the announcement showed the three carriers are “nervous,” and pointed to the timing: “You announce an agreement in principle when the point is the announcement, not the deal. The timing, weeks ahead of the SpaceX roadshow, was the point.”

As Teslarati reported, SpaceX’s next generation Starlink V2 satellites will deliver up to 100 times the data density of the current system, with custom silicon and phased array antennas enabling around 20 times the throughput of the first generation. The carriers’ JV, which has no definitive agreement, no financial structure, and no deployment timeline yet, will need to move quickly to matter.

Elon Musk’s SpaceX is targeting a Nasdaq listing as early as June 12, aiming for what would be the largest IPO in history. With Starlink now serving over 9 million subscribers across 155 countries, holding 59 carrier partnerships globally, and now powering Air Force One, the carriers’ joint venture announcement landed at exactly the wrong time to look like anything other than a defensive move.

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Tesla Model Y prices just went up for the first time in two years

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Credit: Tesla Asia | X

Tesla just raised Model Y prices for the first time in two years, with the largest increase being $1,000.

The move signals shifting dynamics in the competitive electric vehicle market as the company continues to work on balancing demand, profitability, and accessibility.

The new pricing affects premium trims while leaving entry-level options unchanged. The Model Y Premium Rear-Wheel Drive (RWD) now starts at $45,990, a $1,000 increase.

The Model Y Premium All-Wheel Drive (AWD)—previously referred to in the post as simply “Model Y AWD”—rises to $49,990, also up $1,000. The top-tier Model Y Performance sees a more modest $500 bump, bringing its starting price to $57,990.

Base models remain untouched to preserve affordability. The entry-level Model Y RWD holds steady at $39,990, and the base Model Y AWD stays at $41,990. This selective approach keeps the crossover accessible for budget-conscious buyers while extracting more revenue from higher-margin configurations.

After years of aggressive price cuts to stimulate volume amid slowing EV adoption and rising competition from rivals like BYD, Ford, and GM, Tesla appears confident in underlying demand. Recent lineup refreshes for the 2026 Model Y, including refreshed styling and efficiency gains, have helped maintain its status as America’s best-selling EV.

By protecting base prices, Tesla avoids alienating price-sensitive customers while improving margins on the more popular variants.

Tesla Model Y ownership review after six months: What I love and what I don’t

For consumers, the changes are relatively modest—under 3% on affected trims—and still position the Model Y competitively against gas-powered SUVs in the same class. Federal tax credits and potential state incentives may further offset costs for eligible buyers.

This marks a subtle but notable shift from the deep discounting era that defined much of 2024 and 2025. As the EV market matures into 2026, Tesla’s pricing strategy will be closely watched for clues about production ramps, new variants like the rumored longer-wheelbase Model Y, and broader profitability goals.

In short, today’s adjustment reflects a company that remains dominant yet pragmatic—willing to test higher pricing where demand supports it. It is unlikely to deter consumers from choosing other options.

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