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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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SpaceX completes another secret Pentagon launch, adding to suspected Starshield buildout
SpaceX launched the classified USSF-385 mission from Vandenberg, landing its booster on a tenth flight.
SpaceX launched another classified mission for the U.S. Space Force from California early Saturday morning, and the Falcon 9 booster that carried it landed on a drone ship in the Pacific for the tenth time. The USSF-385 mission lifted off from Space Launch Complex 4E at Vandenberg Space Force Base at 7:00 a.m. PT.
Booster B1100 touched down on Of Course I Still Love You roughly eight and a half minutes after liftoff. It was the booster’s tenth flight and tenth successful landing, following the NROL-95 national security mission and eight Starlink launches. Its previous flight, a Starlink Group 15 mission on August 22, came just 35 days earlier. SpaceX ended its livestream shortly after the landing, which is standard for classified payloads, and neither the company nor the Space Force has said what the rocket carried.
Watch Falcon 9 launch the USSF-385 mission from pad 4E in California https://t.co/CAdbx85Ydy
— SpaceX (@SpaceX) September 26, 2026
USSF-385 is the fourth Space Force launch from the same Vandenberg pad in roughly six weeks, following USSF-366 on August 15, USSF-153 on September 10, and USSF-259 on September 17. When SpaceX flew USSF-366 in August, independent trackers noted that the rocket’s stage drop zones matched SpaceX’s Starlink Group 15 missions, pointing to Starshield, the government version of the Starlink satellite bus. The Space Force later cataloged 23 satellites after both USSF-366 and USSF-153, while USSF-259 placed 17 satellites into a different orbital plane, per KeepTrack. Launch databases describe USSF-385 the same way, though the payload remains officially unidentified.
The cadence lines up with the contracts, because in July, the Space Force awarded SpaceX $1.6 billion in task orders for 18 Falcon 9 missions from Vandenberg through the end of 2027. SpaceX also holds contracts to build pieces of that same network, which pushed its Pentagon contract total for 2026 past $8 billion.
Saturday’s flight was also the sixth and final Falcon 9 launch from Vandenberg in September, according to Spaceflight Now, while only one Falcon 9 flew from the East Coast this month as SpaceX shifts its Florida infrastructure toward Starship. Launch trackers list it as SpaceX’s 112th mission of 2026 and the 108th Falcon 9 flight of the year, with SLC-4E turned around about six and a half days after its previous launch.
The West Coast pad will not stay quiet for long, considering SpaceX has another Starlink mission scheduled from SLC-4E on September 30. Meanwhile, in Texas, the company is two days away from Starship Flight 14, which is targeting Monday at 7:15 a.m. CT for the vehicle’s first attempt to reach orbit.
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Tesla hints at new Roadster design in surprise clip
Tesla ended its Semi event with a Roadster teaser revealing a new front light bar.
Tesla closed out its Semi event in Nevada on Thursday night with a nod to its own history, dropping a short Roadster teaser that suggests the production car will look noticeably different from the prototype first shown in 2017.
“We can’t have a Semi event without the Roadster,” Tesla engineering executive Lars Moravy told the crowd before the clip played. The line was a deliberate callback. Tesla first revealed the next generation Roadster in November 2017 by driving it out of the back of a Semi trailer at the truck’s original unveiling in Hawthorne, California.
The new video opens on trailer doors swinging apart in the dark. A thin white light bar glows across what appears to be the nose of the car, Tesla and SpaceX logos flash over the frame, and the Roadster name appears before the clip ends on “See you next week.” Tesla posted the nine second clip on X after the livestream wrapped.
See you next week pic.twitter.com/BT52bGVxFu
— Tesla (@Tesla) September 25, 2026
The light bar is the most concrete design detail so far. The 2017 prototype used two separate curved headlamp pods, while a connected front light strip would bring the Roadster in line with the Cybertruck, Cybercab, Semi, and refreshed Model Y. Sawyer Merritt was among the first to point out what looked like part of a SpaceX logo in the video, something Tesla has not addressed.
That logo fits the buildup around the optional SpaceX Package, which Elon Musk has long said would use cold gas thrusters to improve acceleration and possibly allow the car to briefly leave the ground. Tesla’s “Go for launch” post on September 12 set the October 1 date, and invitations sent to reservation holders place the event in Waco, Texas, at 8:30 p.m. Eastern. Waco sits roughly 20 minutes from SpaceX’s McGregor rocket test site, where the FAA has put a temporary flight restriction in place from September 18 through October 2, covering a 1.5 nautical mile radius from the surface up to 10,000 feet.
Tesla is also taking money ahead of the reveal. The company reopened Roadster reservations earlier this week with a $5,000 refundable card payment, followed by a $45,000 wire transfer due within 10 days. That puts buyers at $50,000 committed before Tesla has published a price.
The original pitch set a high bar: 0 to 60 mph in 1.9 seconds before any upgrades, 620 miles of range, a top speed above 250 mph, and production in 2020. That timeline has slipped repeatedly, and Tesla has since pointed to production at Gigafactory Texas no earlier than 2027. The company has said next Thursday’s event will include pricing, specifications, and production targets, the three details original reservation holders have been waiting on for nearly nine years.
Tesla Full Self-Driving’s release in Europe is set to be delayed by at least a few months.
The European Union will not vote on Tesla’s Full Self-Driving (Supervised) on October 6. The draft agenda for the 119th meeting of the Technical Committee on Motor Vehicles lists only a 25-minute “continuation of discussions” on the Netherlands’ Article 39 request, not a decision. The next scheduled TCMV session is in December, which is now the earliest date a bloc-wide vote could occur.
Tesla Europe had pointed to October 6 as a possible EU-wide vote after the Dutch vehicle authority RDW granted the first European type approval on April 10.
That approval, under UN Regulation 171 plus an Article 39 exemption in EU Regulation 2018/858, is the legal file other member states have been recognizing one by one. The same committee has already discussed the request twice without voting.
Elon Musk’s reply to the delay was a single word: “Sigh.”
Sigh
— Elon Musk (@elonmusk) September 25, 2026
Seven EU countries have now cleared FSD Supervised on their own roads: the Netherlands, Lithuania, Estonia, Denmark, Belgium, Slovenia, and Czechia. Those seven states represent about 53 million people, or roughly 12 percent of the EU population. An EU-wide authorization still needs a qualified majority: at least 15 of 27 member states representing 65 percent of the bloc’s population, about 292 million people.
Germany, France, Italy, and Spain remain the decisive markets. France has already rejected the current system; several other governments have flagged speed-limit compliance as the main sticking point.
The safety case Tesla is putting in front of those governments is now public. On September 1, Tesla Europe said FSD Supervised was in use by more than 70,000 customers, covering over 1 million kilometers a day, and was 4.1 times less likely to be involved in a crash than manual driving across 100 million kilometers on EU public roads.
An earlier mid-year cut of the same fleet data, covering 65 million kilometers in five approved countries, put the collision advantage at 5.2 times, with zero highway collisions over 41.9 million kilometers. Tesla also reported far fewer automatic emergency braking events, harsh accelerations, and hard swerves than in comparable manual Tesla driving. Those figures are company-reported, not independently audited.
Tesla Full Self-Driving is taking over Europe: fourth country gets FSD approval
The public-health backdrop is harder to dispute. European countries recorded about 19,400 road deaths in 2025, or roughly 53 a day, most of them attributed to human error. FSD Supervised is not unsupervised autonomy; the driver remains legally responsible. But the software is already legal and in daily use across seven member states.
Until TCMV votes, the rest of the EU remains a patchwork: available in Prague and Amsterdam, locked behind review in Paris and Berlin. December is now the next chance to close that gap.
SpaceX completes another secret Pentagon launch, adding to suspected Starshield buildout
Tesla hints at new Roadster design in surprise clip
