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Tesla FSD Beta 10.69.2.2 extending to 160k owners in US and Canada: Elon Musk
It appears that after several iterations and adjustments, FSD Beta 10.69 is ready to roll out to the greater FSD Beta program. Elon Musk mentioned the update on Twitter, with the CEO stating that v10.69.2.2. should extend to 160,000 owners in the United States and Canada.
Similar to his other announcements about the FSD Beta program, Musk’s comments were posted on Twitter. “FSD Beta 10.69.2.1 looks good, extending to 160k owners in US & Canada,” Musk wrote before correcting himself and clarifying that he was talking about FSD Beta 10.69.2.2, not v10.69.2.1.
While Elon Musk has a known tendency to be extremely optimistic about FSD Beta-related statements, his comments about v10.69.2.2 do reflect observations from some of the program’s longtime members. Veteran FSD Beta tester @WholeMarsBlog, who does not shy away from criticizing the system if it does not work well, noted that his takeovers with v10.69.2.2 have been marginal. Fellow FSD Beta tester @GailAlfarATX reported similar observations.
Tesla definitely seems to be pushing to release FSD to its fleet. Recent comments from Tesla’s Senior Director of Investor Relations Martin Viecha during an invite-only Goldman Sachs tech conference have hinted that the electric vehicle maker is on track to release “supervised” FSD around the end of the year. That’s around the same time as Elon Musk’s estimate for FSD’s wide release.
It should be noted, of course, that even if Tesla manages to release “supervised” FSD to consumers by the end of the year, the version of the advanced driver-assist system would still require drivers to pay attention to the road and follow proper driving practices. With a feature-complete “supervised” FSD, however, Teslas would be able to navigate on their own regardless of whether they are in the highway or in inner-city streets. And that, ultimately, is a feature that will be extremely hard to beat.
Following are the release notes of FSD Beta v10.69.2.2, as retrieved by NotaTeslaApp:
– 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 connectivities. 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.
– 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 maneuvers.
– 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 optimisable 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.
– 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.
– 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.
– 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.
– 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.
– Made speed profile more comfortable when creeping for visibility, to allow for smoother stops when protecting for potentially occluded objects.
– Improved recall of animals by 34% by doubling the size of the auto-labeled training set.
– 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.
– 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.
– Improved speed when entering highway by better handling of upcoming map speed changes, which increases the confidence of merging onto the highway.
– Reduced latency when starting from a stop by accounting for lead vehicle jerk.
– Enabled faster identification of red light runners by evaluating their current kinematic state against their expected braking profile.
Press the “Video Record” button on the top bar UI to share your feedback. When pressed, your vehicle’s external cameras will share a short VIN-associated Autopilot Snapshot with the Tesla engineering team to help make improvements to FSD. You will not be able to view the clip.
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Tesla is staging a powerful rebound in Europe. New vehicle registrations surged dramatically across multiple key markets in May 2026, signaling a strong recovery from the challenges of 2025.
Data released this week show double- and triple-digit year-over-year gains in several countries, driven by refreshed Model Y production, supportive policies, high fuel prices, and renewed consumer interest in electric vehicles.
In France, registrations exploded 655 percent to 5,446 vehicles, marking Tesla’s best May performance ever in the country. Norway, a longtime EV stronghold, saw 3,345 new Teslas registered, up 29 percent from May 2025. The company even captured a commanding 21.5 percent market share there, according to Detroit News.
Growth extended to other markets as well. Sweden posted a 71 percent increase to 858 registrations. Denmark jumped 136 percent to 1,750 units, where the Model Y became the top-selling vehicle overall. Spain climbed 113 percent to 1,690 sales, while Portugal soared nearly 350 percent to 1,463.
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Tesla Full Self-Driving expansion in Europe continues with new addition
The May results build on a broader turnaround for Tesla in Europe. The company’s sales on the continent had declined sharply in 2025, dropping between 27 and 28 percent amid production shifts, intense competition from Chinese rivals like BYD, and shifting consumer sentiment.
Early 2026 showed signs of life, with registrations rising about 45 percent across Europe in the first quarter and continuing upward momentum through April, up over 46 percent region-wide.
Europe’s overall electrified vehicle market (including BEVs, PHEVs, and hybrids) grew about 21 percent in May, providing a favorable tailwind. Tesla’s gains align with this trend, boosted by government incentives and high fuel costs that make EVs more attractive.
Earlier data from March and April already hinted at strength in Germany, where registrations had surged dramatically in prior months.
Analysts note that while competition remains fierce, Tesla’s refreshed lineup and Europe’s policy support for EVs are helping the company regain ground. The May surge suggests the worst of the 2025 downturn may be behind it, positioning Tesla for stronger performance in the second half of 2026.
This rebound is welcome news for the EV pioneer, demonstrating resilience in a competitive and evolving market. As more data rolls in, investors and industry watchers will be closely monitoring whether this momentum can sustain through the summer and beyond.
Tesla is planning to improve one of the best features on its lineup of cars, a new patent shows. Tesla’s massive glass roof on its premium models is among the coolest additions to the all-electric vehicles, but the design certainly has its complaints, especially from those who live in even slightly warm climates.
Tesla has published a new patent that promises to transform cabin comfort in its electric vehicles, particularly those equipped with the expansive glass roofs.
The document, identified as US20260091643A1 and titled “Airflow Optimization for Cabin Comfort“, addresses that common complaint. Sunlight streaming through windshields and panoramic roofs creates localized hot air pockets near the dashboard and headliner. These pockets generate significant temperature gradients that conventional heating, ventilation, and air conditioning systems struggle to manage evenly.
The exposure to direct sunlight can make the cabin extremely warm, and even after cooling down the interior temperature, combating the continuous stream of sunlight and heat is a challenge. It uses precious energy that is especially pertinent to range and efficiency.
The patent explains how standard dashboard vents push cool air upward, only to entrain warmer air from these stagnant zones and distribute it throughout the occupied cabin space. This process forces the blower to operate at higher speeds, increasing energy consumption and reducing overall efficiency.
In electric vehicles, where every watt impacts driving range, such inefficiencies prove costly.
🚨 THE MODEL Y L IS THE MOST WATCHED EV LAUNCH OF 2026. ITS GLASS ROOF HAS ONE WEAKNESS — AND A PATENT PUBLISHED THIS WEEK SHOWS @TESLA BUILT THE FIX
The Model Y L launched in China and is now arriving in Korea, Japan, and across Asia-Pacific. It also has a glass roof. So does… https://t.co/wr6XnBn1Oc pic.twitter.com/5sYpniXJbU
— SETI Park (@seti_park) April 5, 2026
Research from AAA indicates that air conditioning can diminish range by up to 17 percent under hot conditions. Tesla’s innovation shifts the approach by extracting heat at its source rather than attempting to dilute it after mixing occurs.
Engineers describe a suction HVAC unit connected to dedicated intakes positioned strategically on the upper dashboard surface and within the headliner.
These intakes link to a hot air pocket extraction duct that channels the warmest air directly into the system’s plenum for conditioning. As the blower activates, it simultaneously draws recirculated cabin air and targeted hot pocket air through filters and cooling coils before redistributing conditioned airflow.
It seems somewhat reminiscent of the Tesla heat pump, which aims to combat colder temperatures.
Tesla highlights Model Y’s heat pump innovations in new promotional video
This method reduces entrainment, lowers peak temperatures, and achieves more uniform comfort levels. Testing data reveals that facial temperature gradients drop from 21 degrees Celsius, or 69.8 degrees Fahrenheit, in conventional setups to just 12 degrees Celsius (53.6 degrees F) with the new system. Blower speeds and compressor power requirements decrease appreciably as a result.
The design incorporates smart controls that monitor sunlight intensity and internal temperature distributions in real time. Suction activates selectively only where needed, optimizing energy use without constant high demand. Furthermore, the extraction duct serves a dual purpose.
In the summer months, it pulls hot air inward for cooling; in winter, it reverses to direct warm air outward for rapid windshield defrosting. This versatility allows the reuse of existing hardware with minimal modifications, potentially enabling retrofits in current Tesla fleets.
Lifestyle
Tesla saves its passengers again – This time after a 300-foot cliff fall in Malibu
A Tesla Model 3 fell 300 feet off a Malibu cliff and both passengers survived.
A Tesla Model 3 plunged roughly 300 feet off a cliff on Mulholland Highway in Malibu on Friday morning, May 29, 2026, and both occupants survived. The crash was reported at approximately 7:30 a.m. near the 2500 block of Mulholland Highway, triggering a multi-agency rescue operation involving Malibu Search and Rescue, the Los Angeles County Fire Department, the California Highway Patrol, and McCormick Ambulance.
When first responders arrived, the male driver was outside the vehicle shouting for help while the female passenger remained pinned inside the Tesla. Rescue crews rappelled down the cliffside on ropes to reach the wreckage. A flight medic was lowered by helicopter to begin treating both victims, and the driver was hoisted up to the roadway before crews used the Jaws of Life to free the trapped passenger. Both were airlifted to a local trauma center with moderate injuries despite a remarkable result for a fall that steep.
The outcome is not surprising, considering Model 3 earned an overall 5-star rating from NHTSA in every category and sub-category, and recorded the lowest probability of injury of any car ever evaluated by the U.S. New Car Assessment Program. The absence of a traditional engine in the front of the vehicle creates a longer crumple zone that absorbs impact energy before it reaches occupants, and the battery pack running along the floor gives the car an unusually low center of gravity that reinforces structural rigidity.
This is not the first time a Tesla has kept passengers alive after going off a cliff. A Tesla Model Y carrying a family of four survived a plunge off a cliff at Devil’s Slide near San Francisco in January 2023, with two adults and two children walking away from a 250-foot fall. That incident drew widespread attention to how the structural integrity of Tesla’s electric platform performs in extreme crash scenarios that most vehicles would not survive.
Tesla Model Y driver who drove off cliff with family attempts to avoid criminal conviction
Tesla’s European Comeback: Registrations soar in May as recovery gains momentum
Tesla plans ingenious improvement to one of its best features
