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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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Elon Musk

Tesla launches 200mph Model S “Gold” Signature in invite-only purchase

Tesla’s final 350-unit Signature Edition closes the book on two cars that changed everything.

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Tesla has announced a super limited Signature Edition run of 250 Model S Plaid and 100 Model X Plaid units as an invite only purchase in a bid to give its original flagship vehicles a proper send-off.

When the Model S first launched in 2012, the first 1,000 units sold were “Signature” editions that required a $40,000 deposit and cost nearly $100,000 each. Those early buyers were Tesla’s first real believers. This new Signature Edition deliberately echoes that moment, bookending a 14-year run with numbered collector hardware.

Both models are finished in an exclusive Garnet Red paint not available on any current Tesla production vehicle, with gold Tesla T badges up front, a gold Plaid badge and Signature badge at the rear, and a white Alcantara interior featuring gold Plaid seat badges, gold piping, Signature-marked door sills, and a numbered dash plate. The Model S adds carbon ceramic brakes with gold calipers. Every unit ships with Tesla’s Luxe Package, bundling Full Self-Driving (Supervised), four years of Premium Service, free lifetime Supercharging, and a Signature Edition key fob. Both are priced at $159,420, a roughly $35,000 premium over standard Plaid inventory.

The discontinuation is part of a broader strategic shift. At Tesla’s Q4 2025 earnings call, Musk described the decision as “slightly sad” but necessary, saying: “It’s time to basically bring the Model S and X programs to an end with an honorable discharge, because we’re really moving into a future that is based on autonomy.”

The Fremont factory floor that built these cars is being converted to manufacture Optimus humanoid robots, with a target of one million units annually.

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Elon Musk

Tesla FSD in Europe vs. US: It’s not what you think

Tesla FSD is approved in the Netherlands, but the European version differs from what US drivers use.

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Tesla FSD 14.3 [Credit: TESLARATI)

On April 10, 2026, the Dutch vehicle authority RDW granted Tesla the first European type approval for Full Self-Driving Supervised, making the Netherlands the first country on the continent to authorize Tesla’s semi-autonomous system for customer use on public roads.

As Teslarati reported, the RDW approval followed 18 months of testing, more than 1.6 million kilometers driven on EU roads, 13,000 customer ride-alongs, and documentation covering over 400 compliance requirements. Tesla Europe had been running public demo drives through cities like Amsterdam and Eindhoven since early 2026, giving passengers their first experience of the system on European streets.


The European version of FSD is not the same software US drivers use. The RDW’s own statement is direct, noting that the software versions and functionalities in the US and Europe “are therefore not comparable one-to-one.” We’ve compile a table below that captures the most significant differences between US-based Tesla FSD vs. European Tesla FSD that’s based on what regulators and Tesla have publicly confirmed.

Feature FSD US FSD Europe (Netherlands)
Regulatory framework Self-certification, post-market oversight Pre-market type approval required (UN R-171 + Article 39)
Hands requirement Hands-off permitted on highway Hands must be available to take over immediately
Auto turning from stop lights Available — navigates intersections, turns, and traffic signals autonomously Available in EU build — confirmed in Amsterdam demo footage handling unprotected turns and signalized intersections
Driving modes Multiple profiles including a more aggressive “Mad Max” mode EU build is more conservative by default and errs on the side of restraint when it cannot confirm the limit
Summon Available — Smart Summon navigates parking lots to driver Status unclear — not confirmed as part of the RDW-approved feature set; urban FSD approval targeted separately for 2027
Driver monitoring Camera-based eye tracking Stricter continuous monitoring with more frequent intervention alerts
Software version FSD v14.3 EU-specific builds that must be separately validated by RDW
Geographic restriction US, Canada, China, Mexico, Australia, NZ, South Korea Netherlands only; EU-wide vote pending summer 2026
Subscription price $99/month €99/month
Full urban FSD scope Available Partial — separate urban application planned for 2027

The approval comes as Tesla is under real pressure to grow FSD subscriptions globally. Musk’s 2025 CEO compensation package, approved by shareholders, includes a milestone requiring 10 million active FSD subscriptions as one condition for his stock awards to vest. Tesla hit one million subscriptions during its Q4 2025 earnings call, which is a meaningful start, but still a long way from the target. Opening Europe as a market for subscriptions, rather than just hardware sales, directly accelerates that number.

Tesla has said it anticipates EU-wide recognition of the Dutch approval during summer 2026, which would extend FSD access to Germany, France, and other major markets through a mutual recognition process without each country repeating the full 18-month review. That timeline is Tesla’s projection, not a confirmed regulatory outcome. As Musk acknowledged at Davos in January 2026, “We hope to get Supervised Full Self-Driving approval in Europe, hopefully next month.”

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Tesla’s troublesome Auto Wipers get a major upgrade

Tesla has quietly deployed a major over-the-air (OTA) update across its entire fleet, implementing a new patent that could finally solve one of the most complained-about features in its vehicles: the Auto Wipers.

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One of Tesla’s most complained-about features is that of the Auto Wipers, but they have recently received a major upgrade that impacts every vehicle in the company’s fleet, a company executive confirmed.

Tesla has quietly deployed a major over-the-air (OTA) update across its entire fleet, implementing a new patent that could finally solve one of the most complained-about features in its vehicles: the Auto Wipers.

Confirmed by senior Tesla AI engineer Yun-Ta Tsai on April 10, the improvement is based on patent US 20260097742 A1. It introduces an “energy balance model” that adds a tactile, physics-driven layer to the existing camera-based system—without requiring any new hardware.

Tesla drivers have griped about auto wipers since the company ditched traditional rain sensors in favor of Tesla Vision around 2018.

Owners routinely report the wipers failing to activate in light drizzle or mist, leaving windshields streaked and visibility dangerously reduced. Just as often, they formerly blasted into high-speed mode on dry, sunny days, screeching across glass and risking scratches or premature blade wear.

This is a rare occurrence anymore, but many owners still report the feature having the wipers perform at the incorrect speed or frequency when precipitation is falling.

Tesla has tried repeatedly to fix the problem through software alone.

Early “Deep Rain” initiatives and the 2023 Autowiper v4 update used multi-camera video and refined neural networks, with Elon Musk promising “super good” performance. The 2024.14 update added manual sensitivity boosts, and later FSD versions claimed further gains. Yet complaints persisted.

Elon Musk apologizes for Tesla’s quirky auto wipers, hints at improvements

Vision systems struggle with edge cases—glare, bugs, reflections, or faint mist—because they rely purely on visual inference rather than physical detection

The new patent takes a different approach. The car’s computer constantly measures electrical power delivered to the wiper motor. It subtracts predictable losses—internal motor friction, linkage drag, and aerodynamic resistance—leaving only the friction force between the rubber blade and windshield glass.

Water lubricates the glass, sharply reducing friction; dry or icy surfaces increase it dramatically. This real-time “tactile” data acts as an independent check on the camera’s visual cues, instantly shutting down false triggers on dry glass and fine-tuning speed for actual rain.

The system can also detect ice and auto-activate defrost heaters, while long-term friction trends alert drivers when blades need replacing.

By fusing vision with precise motor-load physics, Tesla has created a hybrid sensor that is both elegant and cost-free. Owners have waited years for reliable auto wipers; this OTA rollout may finally deliver them.

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