News
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.
Don’t hesitate to contact us with news tips. Just send a message to simon@teslarati.com to give us a heads up.
Cybertruck
Chattanooga Charge: Tesla and EV fans ready for the Southeast’s wildest Tesla party
From Cybertruck Convoys to Kid-Friendly Fun Zones: The Chattanooga Charge Has Something for Everyone
Hundreds of like-minded Tesla and EV enthusiasts are descending on Chattanooga Charge this weekend for the largest Tesla meet in the Southeast. Taking place on March 20–22, 2026 at the stunning Tennessee Riverpark.
If you were there last year, you’ll know that it’s the ultimate experience to see the wildest Teslas in action, see the best in EV tech, and arguably the most fun – finally put a name to the face and connect with those social media buddies IRL! Oh, and that epic night time Tesla light show is a once-in-a-lifetime experience that will transform the Riverpark into something out of a sci-fi film that’s remarkably unforgettable and must be seen in person.
This year’s event takes everything up a notch, with over 100 Cybertrucks expected to be on display, many sporting jaw-dropping modifications and custom wraps that push the boundaries of what these stainless steel beasts can look like.
Whether you’re a diehard Tesla fan, EV supporter, or just EV-mod-curious, the sheer spectacle is worth the drive.
The Chattanooga Charge doesn’t wait until Saturday morning to get started. The weekend technically kicks off Friday, March 20th, and the venue sets the tone immediately. Come share roadtrip stories over drinks at the W-XYZ Rooftop Bar on the top floor of the Aloft Chattanooga Hamilton Place Hotel, with sunset views over the city.
Come morning, nurse your hangover with a some good coffee, and convoy with hundreds of other Tesla and EV drivers through Chattanooga to the event for some morning meet and greets before the speaker panel starts and the food trucks fire up.
Tesla owner clubs travel from across the country to be here, not just to show off their vehicles,, but to connect, share, and celebrate a shared passion for the future of driving.
Sounds like a plan to me. See you there, guys. Don’t miss it. Get your tickets at ChattanoogaCharge.com and join the charge. 🔋⚡
Chattanooga Charge is a premier Tesla and EV gathering inspired by the X Takeover, known as one of the largest Tesla event gatherings. What began as a bold idea from the team at DIY Wraps/TESBROS, hosted in their hometown of Chattanooga, Tennessee, the event quickly became a movement across social media. The first annual Chattanooga Charge united over 16 Tesla clubs from 16 states, proof that the EV community was hungry for something big in the South. Year after year, the event has grown in scale, ambition, and heart.
News
Tesla Full Self-Driving gets latest bit of scrutiny from NHTSA
The analysis impacts roughly 3.2 million vehicles across the company’s entire lineup, and aims to identify how the suite’s degradation detection systems work and how effective they are when the cars encounter difficult visibility conditions.
The National Highway Traffic Safety Administration (NHTSA) has elevated its probe into Tesla’s Full Self-Driving (Supervised) suite to an Engineering Analysis.
The analysis impacts roughly 3.2 million vehicles across the company’s entire lineup, and aims to identify how the suite’s degradation detection systems work and how effective they are when the cars encounter difficult visibility conditions.
The step up into an Engineering Analysis is often required before the NHTSA will tell an automaker to issue a recall. However, this is not a guarantee that a recall will be issued.
🚨 The NHTSA said it was upgrading a probe into Tesla’s Full Self-Driving (Supervised) platform to an “engineering analysis”
It will examine 3.2 million vehicles and aims to determine its effectiveness in evaluating degraded road conditions pic.twitter.com/2dkrv1mR8o
— TESLARATI (@Teslarati) March 19, 2026
The NTHSA wants to examine Tesla FSD’s ability to assess road conditions that have reduced visibility, as well as detect degradation to alert the driver with sufficient time to respond.
The Office of Defects Investigation (ODI) will evaluate the performance of FSD in degraded roadway conditions and the updates or modifications Tesla makes to the degradation detection system, including the timing, purpose, and capabilities of the updates.
Tesla routinely ships software updates to improve the capabilities of the FSD suite, so it will be interesting to see if various versions of FSD are tested. Interestingly, you can find many examples from real-world users of FSD handling snow-covered roads, heavy rain, and single-lane backroads.
However, there are incidents that the NHTSA has used to determine the need for this probe, at least for now. The agency said:
“Available incident data raise concerns that Tesla’s degradation detection system, both as originally deployed and later updated, fails to detect and/or warn the driver appropriately under degraded visibility conditions such as glare and airborne obscurants. In the crashes that ODI has reviewed, the system did not detect common roadway conditions that impaired camera visibility and/or provide alerts when camera performance had deteriorated until immediately before the crash occurred.”
It continues to say in its report that a review of Tesla’s responses revealed additional crashes that occurred in similar environments showed FSD “did not detect a degraded state, and/or it did not present the driver with an alert with adequate time for the driver to react. In each of these crashes, FSD also lost track of or never detected a lead vehicle in its path.”
The next steps of the NHTSA Engineering Analysis require the agency to gather further information on Tesla’s attempts to upgrade the degradation detection system. It will also analyze six recent potentially related incidents.
The investigation is listed as EA26002.
Elon Musk
SpaceX’s Starship V3 is almost ready and it will change space travel forever
SpaceX is targeting April for the debut test launch of Starship V3 “Version 3”
SpaceX is closing in on one of the most anticipated rocket launches in history, as the company readies for a planned April test launch and debut of its next-gen Starship V3 “Version 3”.
The latest iteration of Starship V3 has a slightly taller Super Heavy booster and Starship upper stage than their predecessors, and produce stronger, more efficient thrust using SpaceX’s upgraded Raptor 3 engines. V3 also features increased propellant capacity, targeting a total payload capacity of over 100 tons to low Earth orbit, compared to around 35 tons for its predecessor. With Musk’s lifelong aspiration to colonize Mars one day, the increased payload capacity matters enormously, because Mars missions require moving massive amounts of cargo, fuel, and eventually, people. But the most critical upgrade may be orbital refueling. SpaceX’s entire deep space architecture depends on moving large amounts of propellant in space, and having orbital refueling capabilities turn Starship from just a rocket into a true transport system. Without it, neither the Moon nor Mars is reachable at scale.
Initial Super Heavy V3 and Starbase Pad 2 activation campaign complete, wrapping up several days of testing that loaded cryogenic fuel and oxidizer on a V3 vehicle for the first time. While the 10-engine static fire ended early due to a ground-side issue, we saw successful… pic.twitter.com/uHGji17srv
— SpaceX (@SpaceX) March 18, 2026
A fully reusable Starship and Super Heavy, SpaceX aims to drive marginal launch costs down and at a tenfold reduction compared to current market leaders. To put that in perspective, getting a kilogram of cargo to orbit today costs thousands of dollars. Bring that number down far enough and space stops being an exclusive domain. That price point unlocks mass deployment of satellite constellations, large-scale science payloads, and affordable human transport beyond Earth orbit. It also means the Moon stops being a destination we visit and starts being one we inhabit.
NASA expects Starship to take off for the Moon’s South Pole in 2028, with the ultimate goal of establishing a permanently crewed science station there. A successful V3 flight this spring keeps that timeline alive. As for Mars, Musk has shifted focus toward building a self-sustaining city on the Moon first, arguing that the Moon can be reached every 10 days versus Mars’s 26-month alignment window. Mars remains the horizon, but the Moon is the proving ground.
Elon Musk hasn’t been shy with hyping the upcoming Starship V3 launch. In a social media post on Wednesday, he confirmed the first V3 flight is getting closer to launch. SpaceX also announced its initial activation campaign for V3 and Starbase Pad 2 was complete, wrapping up several days of cryogenic fuel testing on a V3 vehicle for the first time. The countdown is on. April can’t come soon enough.
Chattanooga Charge: Tesla and EV fans ready for the Southeast’s wildest Tesla party
Tesla Full Self-Driving gets latest bit of scrutiny from NHTSA
